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Exploiting multi-antennas for opportunistic spectrum sharing in cognitive radio networks
... Under such a constrained environment, the SUs have two conflicting targets of maximizing their throughput and limiting the interference at the PUs. However, SUs can achieve significant throughput by exploiting the resources, such as spatial dimensions, efficiently [28]. ...
... , N t }. Recall the constraint rank(S * ) = 1 in the problem (28) and assume there is a solution f * such that ...
... ≥ τ Nt are the non-negative eigenvalues of S * . Recall the constraint tr (S * ) ≤P t NpL in the problem formulation (28). Substituting in (35), we get ...
With the increasing number of wireless communication systems and the demand for bandwidth, the wireless medium has become a congested and contested environment. Operating under such an environment brings several challenges, especially for military communication systems, which need to guarantee reliable communication while avoiding interfering with other friendly or neutral systems and denying the enemy systems of service. In this work, we investigate a novel application of Rate-Splitting Multiple Access (RSMA) for joint communications and jamming with a Multi-Carrier (MC) waveform in a multi-antenna Cognitive Radio (CR) system. RSMA is a robust multiple access scheme for downlink multi-antenna wireless networks. RSMA relies on multi-antenna Rate-Splitting (RS) strategy at the transmitter and Successive Interference Cancellation (SIC) at the receivers. By employing RSMA at the secondary transmitter, our aim is to simultaneously communicate with Secondary Users (SUs) and jam Adversarial Users (AUs) to disrupt their communications while limiting the interference to Primary Users (PUs) in a setting where all users perform broadband communications by MC waveforms in their respective networks. We consider the practical setting of imperfect CSI at Transmitter (CSIT) for the SUs and PUs, and statistical CSIT for AUs. We formulate a problem to obtain optimal precoders which maximize the mutual information under interference and jamming power constraints. We propose an Alternating Optimization-Alternating Direction Method of Multipliers (AO-ADMM) based algorithm for solving the resulting non-convex problem. We perform an analysis based on Karush-Kuhn-Tucker (KKT) conditions to determine the optimal jamming and interference power thresholds that guarantee the feasibility of problem and propose a practical algorithm to calculate the interference power threshold. By simulation results, we demonstrate that RSMA achieves a higher sum-rate performance than Space Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA).
... • Next, we further study the SE maximization problem based on the exact achievable rate expression under the same constraints above. By exploiting the Karush-Kuhn-Tucker (KKT) conditions and the relationship between the mutual information and the minimum mean-squared error (MMSE) 1 [21], we propose a multi-level mercurywater-filling power allocation scheme to achieve the maximum of SE [22], [23]. It is shown that the power allocation behaves differently with respect to the channel gain in the low and high power domains. ...
... which can obtained by the multi-level mercury-water-filling power allocation scheme as listed in Algorithm 1 [22], [23]. Moreover, to facilitate the explanation of the power allocation scheme, an auxiliary function G i (λ 1 , λ 2 ) is defined as follows (40). ...
... Thus, the original joint optimization problem (43) is converted into a concave-concave fractional problem, which is still complex and hard to solve. To overcome this challenge, P dc in (44) is reformulated based on the Cauchy-Schwarz inequality (22) and is given by ...
The bound of the information transmission rate of direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) for visible light communication (VLC) with finite-alphabet inputs is yet unknown, where the corresponding spectral efficiency (SE) and energy efficiency (EE) stems out as the open research problems. In this paper, we derive the exact achievable rate of {the} DCO-OFDM system with finite-alphabet inputs for the first time. Furthermore, we investigate SE maximization problems of {the} DCO-OFDM system subject to both electrical and optical power constraints. By exploiting the relationship between the mutual information and the minimum mean-squared error, we propose a multi-level mercury-water-filling power allocation scheme to achieve the maximum SE. Moreover, the EE maximization problems of {the} DCO-OFDM system are studied, and the Dinkelbach-type power allocation scheme is developed for the maximum EE. Numerical results verify the effectiveness of the proposed theories and power allocation schemes.
... • Next, we further study the SE maximization problem based on the exact achievable rate expression under the same constraints above. By exploiting the Karush-Kuhn-Tucker (KKT) conditions and the relationship between the mutual information and the minimum mean-error (MMSE) 1 [21], we propose a multi-level mercury-water-filling power allocation scheme to achieve the maximum of SE [22], [23]. It is shown that the power allocation behaves differently with respect to the channel gain in the low and high power domains. ...
... Applying the inequality (22), the upper bound of the total electrical transmitted power (25) is ...
... Algorithm 1 [22], [23]. Moreover, to facilitate the explanation of the power allocation scheme, an auxiliary function G i (λ 1 , λ 2 ) is defined as follows: ...
The bound of the information transmission rate of direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) for visible light communication (VLC) with finite-alphabet inputs is yet unknown, where the corresponding spectral efficiency (SE) and energy efficiency (EE) stems out as the open research problems. In this paper, we derive the exact achievable rate of the DCO-OFDM system with finite-alphabet inputs for the first time. Furthermore, we investigate SE maximization problems of the DCO-OFDM system subject to both electrical and optical power constraints. By exploiting the relationship between the mutual information and the minimum mean-squared error, we propose a multi-level mercury-water-filling power allocation scheme to achieve the maximum SE. Moreover, the EE maximization problems of the DCO-OFDM system are studied, and the Dinkelbach-type power allocation scheme is developed for the maximum EE. Numerical results verify the effectiveness of the proposed theories and power allocation schemes.
... Also, zero-forcing may result in a distorted beamformer with high sidelobes that increase the background interference level. The resulting optimization problem with receivedinterference power constraints is similar to that encountered in underlay cognitive radio literature [10,11] and can be addressed under a Second-Order Cone Programming (SOCP) formulation. However, the resulting optimization procedure is rather inappropriate for real-time application since it requires iterative solving procedures. ...
... where λ denotes the Lagrangian multiplier associated to the constraint (C3). From (11) it is clear that the solution to (10) corresponds to a generalized eigenvalue problem, with the optimal beamforming vector b * k given by the eigenvector associated to the largest eigenvalue λmax of J j=1 ...
... Clearly, ZFB cannot be applied as J > N . We have simulated the optimal solution of (4), the proposed transmit beamforming solution (11), the conventional matched filter given by b k = h H d and the virtual SINR beamformer [12]. Note that Optimal (4) as SOCP in CVX Proposed (11) Fig. 3. Processing time versus number of antennas the last two are not designed to meet the received-interference power constraints (C1) and (C2) of (4). ...
... Following the similar proof of Lemma 2 in [33], we can obtain that the optimal solution to problem (24) is ...
... Notice that the first constraint in problem (33) is a chance constraint, which leads to problem (33) difficult to solve. To deal with this circumstance, we will transform this chance constraint into a deterministic form by applying the Bernstein-type inequality. ...
... By substituting (37) into (33) and dropping the non-convex rank-one constraint, we obtain ...
Cooperative jamming is a widely used approach for improving the security of wireless networks. In this approach, a friendly jammer sends jamming signals to disrupt the reception of the eavesdropper, which inevitably interferes with the legitimate receiver. In this paper, we propose a novel approach, namely, information jamming, to exceed the secrecy rate achieved by the traditional cooperative jamming approach in a multiple-input single-output (MISO) wiretap channel. We propose that multiple multi-antenna information jammers (iJammers) transmit the source signals of the legitimate transmitter rather than independent noise signals for simultaneously enhancing the signal strength at the legitimate receiver and canceling the received signal at the eavesdropper. Specifically, we aim at maximizing the achievable secrecy rate by jointly optimizing the beamforming vectors at Alice and iJammers, subject to the individual transmit power constraints. We first propose a semi-definite relaxation based approach to solve the original non-convex problem optimally. For ease of implementation, we then provide a suboptimal distributed information beamforming scheme, whose optimal solution is obtained in closed-form. Finally, we extend our study to the imperfect channel state information case. Simulation results show that our proposed information jamming approach significantly outperforms the traditional cooperative jamming approach in terms of achievable secrecy rate. Index Terms Physical-layer security, information jamming, secrecy rate, beamforming design.
... In this section, we conduct a brief survey for the related work in three aspects, which includes CR beamforming, robust beamforming, and IRS-assisted wireless communication system. 1) CR Beamforming: So far, a lot of CR beamforming techniques have been designed by assuming that the CSI is perfectly known at SU-TX [5], [6], [28]- [30]. Specifically, in [28], a single SU is considered for spectrum sharing by restricting the interference leakages to each PU. ...
... In this section, we conduct a brief survey for the related work in three aspects, which includes CR beamforming, robust beamforming, and IRS-assisted wireless communication system. 1) CR Beamforming: So far, a lot of CR beamforming techniques have been designed by assuming that the CSI is perfectly known at SU-TX [5], [6], [28]- [30]. Specifically, in [28], a single SU is considered for spectrum sharing by restricting the interference leakages to each PU. For multiple SUs, beamforming techniques are proposed to maximize the minimum signal-to-interference-plus-noise ratio (SINR) and the minimum rate of SUs in [5] and [29], respectively. ...
... This problem however has been widely studied in traditional CR systems. Following [28], if w is a feasible solution of problem (P1.1), then e jθ w for arbitrary θ is also a feasible solution which maintains the same objective value. Thus, problem (P1.1) can be rewritten as an SOCP as follows: ...
Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users. Meanwhile, intelligent reflecting surface (IRS), also known as reconfigurable intelligent surface (RIS), has been recently proposed as a promising approach to enhance energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. To improve both SE and EE, in this paper, we introduce multiple IRSs to a downlink multiple-input single-output (MISO) CR system, in which a single SU coexists with a primary network with multiple primary user receivers (PU-RXs). Our design objective is to maximize the achievable rate of SU subject to a total transmit power constraint on the SU transmitter (SU-TX) and interference temperature constraints on the PU-RXs, by jointly optimizing the beamforming at SU-TX and the reflecting coefficients at each IRS. Both perfect and imperfect channel state information (CSI) cases are considered in the optimization. Numerical results demonstrate that the introduction of IRS can significantly improve the achievable rate of SU under both perfect and imperfect CSI cases.
... Coming next to the existing contributions on CR systems, fully-digital TPC/RC techniques were designed for the conventional sub-6 GHz MIMO architecture in [28]- [31], [35]- [37]. Zhang et al., derive the SE of a MIMO CR system using the singular value decomposition (SVD) of the SU MIMO channel considering the transmit power constraint at the SU and interference power constraints at multiple PUs. ...
... Similarly, the solution to the optimization problem (28) can be obtained using the SOMP-based simultaneous sparse signal recovery technique, as already discussed in Algorithm 1. Furthermore, in order to mitigate the MUI, one has to design the BB TPC F 2 BB in the second stage. In order to keep the design complexity low, we employ the zero forcing (ZF) technique to determine F 2 BB . ...
A hybrid transceiver architecture is conceived for a cognitive radio (CR) aided millimeter wave (mmWave) multiuser (MU) multiple-input multiple-output (MIMO) downlink system relying on multiple radio frequency (RF) chains both at the CR base station (CBS) and the secondary users (SUs). To begin with, a hybrid transceiver design algorithm is proposed for the CBS and SUs, to maximize the sum spectral efficiency (SE) by decoupling the hybrid transceiver into a blind minimum mean squared error (MMSE) receiver combiner (RC) and optimal-capacity two-stage hybrid transmit precoder (TPC) components. These RC-weights and TPC-weights are subsequently found by using the popular simultaneous orthogonal matching pursuit (SOMP) technique. A closed-form solution is derived for the optimal power allocation that maximizes the sum SE under the associated interference and transmit power constraints. To achieve user fairness, we also propose an optimal power allocation scheme for maximizing the geometric mean (GM) of the SU rates. Finally, a low-complexity limited feedback aided hybrid transceiver is designed, which relies on the random vector quantization (RVQ) technique. Our simulation results demonstrate that an improved SE is achieved in comparison to the state-of-the-art techniques.
... Achieving effective interference suppression and management is a key research topic that attracted significant interest in various systems, such as network MIMO [8], [9], distributed antenna/coordinated multipoint (CoMP) systems [10]- [12], cell free massive MIMO [13]- [15], and spectrum sharing and radar/communication coexistence [16]- [18]. The approaches developed in [8]- [14], [16]- [18], however, considered conventional fully-digital MIMO transceiver architectures where the precoding and combining are implemented completely in the digital domain. ...
... Achieving effective interference suppression and management is a key research topic that attracted significant interest in various systems, such as network MIMO [8], [9], distributed antenna/coordinated multipoint (CoMP) systems [10]- [12], cell free massive MIMO [13]- [15], and spectrum sharing and radar/communication coexistence [16]- [18]. The approaches developed in [8]- [14], [16]- [18], however, considered conventional fully-digital MIMO transceiver architectures where the precoding and combining are implemented completely in the digital domain. With the recent evolution towards high frequency bands (e.g., mmWave and terahertz) and the utilization of even larger antenna arrays, new transceiver architectures (e.g., fully analog and hybrid analog/digital architectures) are introduced to reduce the hardware cost and power consumption. ...
Employing large antenna arrays is a key characteristic of millimeter wave (mmWave) and terahertz communication systems. Due to the hardware constraints and the lack of channel knowledge, codebook based beamforming/combining is normally adopted to achieve the desired array gain. However, most of the existing codebooks focus only on improving the gain of their target user, without taking interference into account. This can incur critical performance degradation in dense networks. In this paper, we propose a sample-efficient online reinforcement learning based beam pattern design algorithm that learns how to shape the beam pattern to null the interfering directions. The proposed approach does not require any explicit channel knowledge or any coordination with the interferers. Simulation results show that the developed solution is capable of learning well-shaped beam patterns that significantly suppress the interference while sacrificing tolerable beamforming/combing gain from the desired user. Furthermore, a hardware proof-of-concept prototype based on mmWave phased arrays is built and used to implement and evaluate the developed online beam learning solutions in realistic scenarios. The learned beam patterns, measured in an anechoic chamber, show the performance gains of the developed framework and highlight a promising machine learning based beam/codebook optimization direction for mmWave and terahertz systems.
... This transmission by SU should be carried out at very low power mode which will not cause any interference to the PU [2]. In order to improve the channel capacity of SU at low power transmission, multiple antennas are deployed in [3]. The beam forming techniques used in MIMO improves the performance of SU significantly [4]. ...
... where max 1 h can be obtained by using equation (3). ...
Transmit antenna selection based multiple antenna systems are widely used in cognitive radio network as it exploits the diversity benefit with less hardware. In underlay mode of cognitive radio, the secondary users have to transmit the signal with tight interference constraints which protect the primary communication. This leads the operation of secondary users at very low power level. In this paper, we proposed the single Transmit Antenna Selection (TAS) technique based on maximal ratio combining for decode-and forward type of relay for image transmission from cognitive radio perspective. We design end-to-end Simulink model for TAS in MIMO cognitive relay network under Rayleigh fading with advancement in channel modelling and relay based feedback system. The received SNR and BER analysis is carried out for with and without relay case for unconstrained secondary transmission of cognitive radio. The performance analysis is done for various MIMO configurations for TAS MIMO relay system.
... To recover this performance loss, advanced techniques that use multiple antennas at the secondary system have been investigated in the literature. They enable multiple spatial streams, exploit spatial diversity, and suppress interference [70][71][72][73][74][75][76]. Compared to a single antenna secondary system, a multiple antenna secondary system is shown to significantly improve the achievable rate [70,72], energy-efficiency [76], outage probability [48,57], and symbol error probability (SEP) [50,51]. ...
... They enable multiple spatial streams, exploit spatial diversity, and suppress interference [70][71][72][73][74][75][76]. Compared to a single antenna secondary system, a multiple antenna secondary system is shown to significantly improve the achievable rate [70,72], energy-efficiency [76], outage probability [48,57], and symbol error probability (SEP) [50,51]. We discuss these techniques in more detail below. ...
Spectrum sharing is essential to support high wireless data rates and a large number of wireless connections by the future technologies in the limited spectrum that is available. In underlay spectrum sharing a secondary user (SU) transmits simultaneously in the same spectrum as the high priority primary user (PU) while ensuring that the interference caused to the PU is constrained. These interference constraints can limit the SU's performance significantly. Transmit antenna selection (TAS) is a low hardware complexity multiple antenna technique that exploits spatial diversity from multiple antennas to improve the SU's performance. In it, the secondary transmitter (STx) selects one among the multiple antennas and connects it to the one available radio frequency chain to transmit. TAS rule specifies the antenna to transmit as a function of the channel gains from the STx to the primary receiver (PRx) and the channel gains from the STx to the secondary receiver. We study the combined impact of the power adaptation technique employed at the STx, interference constraint, and the channel state information (CSI) available at the STx on TAS for underlay spectrum sharing. In this thesis, we focus on characterizing optimal TAS rules that minimize the average symbol error probability (SEP) of an underlay secondary system that is subject to a general class of stochastic interference constraints. This includes the average interference constraint and the interference-outage constraint. We first focus on a secondary system that employs on-off power adaptation at the STx and is subject to the interference-outage constraint. For it, we propose a TAS rule that minimizes the average SEP when the STx shares spectrum with a single PRx and has the instantaneous CSI of the link from it to the PRx. We prove it to be SEP-optimal for a general class of fading models with a continuous cumulative distribution function. We derive expressions for its interference-outage probability and average SEP for both perfect and imperfect CSI. We show that it reduces the average SEP significantly compared to the existing selection rules in the literature. We then generalize the above model to consider the practical scenario in which the SU shares spectrum with multiple PRxs. For it, we develop a TAS rule that minimizes the average SEP when the STx has instantaneous CSI of only a subset of the STx-PRx links. We study the impact of the STx-PRx CSI on the optimal rule by considering the cases when the STx knows channel gains to all the PRxs and when it does not know channel gains to any of the PRxs. We derive expressions for its interference-outage probability and average SEP. We observe that the performance of the optimal rule is insensitive to the interference power threshold when the STx does not know the instantaneous CSI of all the STx-PRx links. Next, we consider a secondary system that employs continuous power adaptation, is subject to the interference-outage and peak transmit power constraints, and shares the spectrum with a single PRx. For it, we present an SEP-optimal joint antenna selection and power adaptation rule that applies to the class of fading models with continuous cumulative distribution function. We show that the optimal rule achieves a one to two orders of magnitude reduction in the average SEP compared to the existing rules in the literature. We then propose a simpler, yet near-optimal, variant called the linear rule. We derive tight bounds for its average SEP and interference-outage probability. Lastly, we study a practically-motivated system model in which the STx only has the statistical information of the links from itself to the PRx. We derive the joint optimal antenna and power adaptation rule for it. We show that it has an intuitive and separable form for the general class of stochastic interference constraints. We evaluate the impact of the power adaptation, interference constraint, and multiple antennas on the performance of the secondary and primary systems.
... s.t. V n,n = 1,n = 1, · · · N + 1 (30b) (29) can be calculated using the CVX and Gaussian randomization [9], and the maximum covert transmission rate is obtained by substituting v * into (29). For this case, no iteration is required. ...
... For the MISO system with covert constraint, we can resort to the traditional MISO cognitive system, which has the interference constraint at the primary user and has a similar optimization objective function. Thus, by leveraging results from MISO cognitive systems in [29], [30], we can derive the optimal beamforming vector as w * = P maxw , wherew denotes the unit-norm beamforming vector and is given bȳ For a given w , Similar to (24), the optimization problem (32) is rewritten as ...
Covert transmission is studied for an intelligent reflecting surface (IRS) aided communication system, where Alice aims to transmit messages to Bob without being detected by the warden Willie. Specifically, an IRS is used to increase the data rate at Bob under a covert constraint. For the considered model, when Alice is equipped with a single antenna, the transmission power at Alice and phase shifts at the IRS are jointly optimized to maximize the covert transmission rate with either instantaneous or partial channel state information (CSI) of Willie's link. In addition, when multiple antennas are deployed at Alice, we formulate a joint transmit beamforming and IRS phase shift optimization problem to maximize the covert transmission rate. One optimal algorithm and two low-complexity suboptimal algorithms are proposed to solve the problem. Furthermore, for the case of imperfect CSI of Willie's link, the optimization problem is reformulated by using the triangle and the Cauchy-Schwarz inequalities. The reformulated optimization problems are solved using an alterative algorithm, semidefinite relaxation (SDR) and Gaussian randomization techniques. Finally, simulations are performed to verify our analysis. The simulation results show that an IRS can degrade the covert transmission rate when Willie is closer to the IRS than Bob.
... Multiple antennas offer a significant potential for doing so in the space domain, especially in the context of massive MIMO [2]. This approach to interference mitigation and control has been investigated earlier in the context of cognitive radio (CR) [3], where secondary users are allowed to use the same bandwidth as primary users (who are the license holders) but are required to cause no significant interference to them. On the other hand, open system architectures and co-existence of several users in the same bandwidth in combination with the broadcast nature of wireless channels make transmissions vulnerable to eavesdropping of confidential information (e.g. ...
... ensures that the total interference power at the jth PR does not exceed the IPC power P Ij so that this PR's performance is not distorted. This type of interference constraints has been widely adopted in the literature for regular systems (no secrecy) [3][49]- [51] as well as for secrecy systems [18][23][27]- [32]. In this multi-user environment, the secrecy capacity of the interference-constrained WTC is defined operationally as the largest achievable rate on the Tx-Rx link subject to the secrecy, reliability, transmit and interference power constraints simultaneously. ...
Multi-user Gaussian MIMO wiretap channel is considered under interference power constraints (IPC), in addition to the total transmit power constraint (TPC). Algorithms for \textit{global} maximization of its secrecy rate are proposed. Their convergence to the secrecy capacity is rigorously proved and a number of properties are established analytically. Unlike known algorithms, the proposed ones are not limited to the MISO case and are proved to converge to a \textit{global} rather than local optimum in the general MIMO case, even when the channel is not degraded. In practice, the convergence is fast as only a small to moderate number of Newton steps is required to achieve a high precision level. The interplay of TPC and IPC is shown to result in an unusual property when an optimal point of the max-min problem does not provide an optimal transmit covariance matrix in some (singular) cases. To address this issue, an algorithm is developed to compute an optimal transmit covariance matrix in those singular cases. It is shown that this algorithm also solves the dual (nonconvex) problems of \textit{globally} minimizing the total transmit power subject to the secrecy and interference constraints; it provides the minimum transmit power and respective signaling strategy needed to achieve the secrecy capacity, hence allowing power savings.
... This requirement can be carefully ignored in the former two paradigms if and only if the PU's channel state information (CSI) is perfectly acquired by SUs [10]- [12]. However, in underlay paradigm, the interference temperature plays a significant role in the achievable data rate of the SUs, which should be carefully handled [13], [14]. Therefore, improving the SUs' data rate in underlay paradigm has been studied extensively, various beamforming and power allocation methods have been proposed [15]- [17]. ...
... To reduce the complexity, here we propose a lowcomplexity algorithm to obtain an optimal closed-form solution with the aid of Lagrange dual decomposition method [40]. Firstly, by introducing the Lagrange multiplier λ associated with the total transmit power, the partial Lagrange function of Problem (13) can be derived as ...
In cognitive radio (CR) systems, the spectrum efficiency (SE) of the secondary users (SUs) is always limited by the interference temperature constraint imposed on the primary users (PUs). Intelligent reflecting surface (IRS) has been recently proposed as a revolutionary technique which can help to enhance the SE of wireless communications. In this paper, we propose to employ an IRS to assist the SUs' data transmission in the multiple-input multiple-output (MIMO) CR system. By jointly optimizing the transmit precoding (TPC) of the SU transmitter (ST) and the phase shifts of the IRS, we aim to maximize the achievable weighted sum rate (WSR) of SUs subject to the ST's total power, the PU's interference temperature and unit modulus constraints. To solve this complicated optimization problem in which the variables are coupled, the block coordinate descent (BCD) algorithm is introduced to alternately solve the subproblems. For each subproblem, the Lagrange dual or inner approximation method is adopted with a low complexity. Simulation results confirm the benefits of employing IRS in a MIMO CR system. The performance comparisons of the proposed algorithm with several other benchmarks are carried out by evaluating the impacts of various parameters on the WSR.
... Iterative waterfilling algorithm [11] involves singular value decomposition at each iteration. Lagrange algorithms [12,13] solve closed-form expressions in terms of iterative dual variables associated with the optimization constraints. Generally speaking, the aforementioned iterative optimization algorithms are by nature computationally expensive. ...
... However, the unfair schemes engage single user underutilizing the spatial degrees of freedom, i.e., single-user MIMO, given that the antenna condition N t ! K holds [9,12]. Thus, the benefit is manifold: better QoS and higher spectral efficiency performance. ...
Spectral efficiency (SE) optimization in massive multiple input multiple output (MIMO) antenna cognitive systems is a challenge originated from the coexistence restrictions. Traditional power allocation can optimize the SE; however, involving deep learning can meet real-time and fairness processing requirements. In unfair allocation problem, all power is possibly assigned to one or few antennas of a particular user. In this paper, we build a mathematical optimization model considering the fairness problem such that SE is optimized for all users. To implement the model, we propose an attention-based convolutional neural network (Att-CNN), where h0 and hk (i.e., cross-interference and direct channels) attention mechanisms are used to improve the SE. The convolutional neural network is applied to decrease the floating point operations (FLOPs) and number of network parameters. We conducted experiments from these aspects: Fair antenna power allocation, power allocation performance and computational performance. Heat maps with different interference thresholds show the fair allocation for all users. Analyses of SE validate the superiority of the Att-CNN compared with the equal power allocation and fully connected neural network (FNN) schemes. The analyses of the FLOPs and number of parameters show the superiority of the Att-CNN over the FNN.
... In addition, it can reduce power consumption by avoiding multiple transmissions required for individual functionality [7,8]. Most of the previous work on JRC systems focuses on architecture design, such as MIMO configurations [9,10], beamforming techniques [11,12], and smart antennas [13]. Similarly, cognitive [14,15] and bio-inspired systems [4,16] were proposed to address spectrum sharing. ...
Due to the increased spectrum congestion, there has been a tremendous interest in radar and communication devices operating on a shared platform. Therefore, the waveform design for joint radar communication (JRC) systems has recently gained significant attention. Despite several efforts, most state-of-the-art waveforms are far from achieving ideal radar and communication performance. To address this issue, we design a family of chaotic maps whose output yields waveforms with optimal JRC features. We adopt the antipodal chaos shift keying (ACSK) scheme, where the segments of the chaotic signal are multiplied by ±1 to encode the binary information. This ACSK waveform is further used for the JRC system transmission. Once the synchronization between the receiver and transmitter is established, the information is recovered by cross-correlating the received and the synchronized waveforms. This technique yields bit error rates (BER) similar to the theoretical values of the BPSK waveform. The same transmitted waveform results in a thumbtack ambiguity function which is essential for high-resolution radar imaging. The variance analysis of the ambiguity function shows that the proposed waveform is comparable to the noise-modulated waveforms. We also show that the multiplexed ACSK waveforms yield similar optimal behavior. Furthermore, we demonstrate the potential of the family of chaotic maps for multiple-input, multiple-output (MIMO) JRC systems.
... To address this issue, both the inter-system and inter-user interference need to be successfully managed. In the standard (non-cognitive) multiuser downlink scenario, beamforming or precoding at the multiantenna transmitter can be employed to mitigate the multiuser interference (MUI) and compensate for its adverse affect on the received signals [6], [7]. Existing precoding schemes can be classified as either block-level precoding (BLP) or symbol-level precoding (SLP). ...
This paper focuses on designing robust symbol-level precoding (SLP) in the downlink of an overlay cognitive radio (CR) network, where a primary base station (PBS) serving primary users (PUs) and a cognitive base station (CBS) serving cognitive users (CUs) share the same frequency band. When the PBS shares data and perfect channel state information (CSI) with the CBS, an SLP approach which minimizes the CR transmission power and satisfies symbol-wise Safety Margin (SM) constraints of both PUs and CUs, is obtained in a low-complexity quadratic formulation. Then for the case of imperfect CSI from the PBS to CBS, we propose robust SLP schemes. First, with a norm-bounded CSI error model to approximate uncertain channels at the PBS, we adopt the max-min philosophy to conservatively achieve robust SLP constraints. Second, we use the additive quantization noise model (AQNM) to describe the statistics of the quantized PBS CSI, and we employ a stochastic constraint to formulate the problem, where the SM constraints are converted to be deterministic. Simulation results show that the proposed robust SLP schemes help enable PUs to mitigate negative effect of the quantization noise and simultaneously offer CR transmission with significant improvements in energy efficiency compared to non-robust methods.
... Moreover, diversity-combining technique has received extensive attention, as it can utilize the characteristics of uncorrelated signals in wireless communication to counteract the fading effect and to improve the link reliability as well as the system throughput [23,24]. And it is also widely considered in HSTRNs [25][26][27][28][29][30][31][32]. ...
Due to the masking effect, a reliable line-of-sight transmission between a satellite and terrestrial nodes is not always guaranteed, and a half-duplex (HD) relaying is commonly performed in literature to assist such transmission. However, the system efficiency could be seriously degraded with the HD relaying as a two-time slot is required for a dual-hop information transmission. Therefore, in this paper, a full-duplex (FD) relaying, which can enable signal receiving and transmitting simultaneously, is considered for a satellite-terrestrial non-orthogonal multiple access (NOMA) system consisting of a multi-antenna satellite source, a FD relay, and two multi-antenna destination nodes. Specifically, the satellite source adopts a maximum ratio transmission scheme to transmit a NOMA signal to the relay, and the relay deploys a decode-and-forward protocol to forward the information to two destination nodes simultaneously, which employ the maximal ratio combining strategy to process the received signals. Assuming the satellite link experiences Shadowed-Rician fading and the terrestrial links undergo Nakagami-m fading distribution, both analytical and asymptotic expressions of outage probability (OP) for two destination nodes are presented in the presence of residual self-interference and imperfect successive interference cancellation. In addition, an adaptive power allocation (APA) scheme is performed, and the system throughput under the delay-limited transmission mode is also analyzed. Finally, Monte-Carlo simulations are adopted to verify the accuracy of those derived analytical expressions. Numerical results show that the OP performance with the FD mode outperforms that with the HD one, and adopting the APA scheme can result in the best OP performance.
... The spatial diversity concept used in multiple-input-multiple-output (MIMO) system can also be considered by using smart antenna technology to avoid interference in heterogeneous CRN for secondary users as presented in [22]. The use of antenna selection concept in MIMO is presented for interference mitigation of secondary CRN users in [23]. ...
The heterogeneous cognitive radio networks are playing the most important role in the future generation wireless networks in order to address the problem of spectrum scarcity and to satisfy the demand of multiple coexistence networks. . In a country like India the deployment of CRN is possible on television network with the help of TV White Spaces (TVWS) as its capacity is quite high due to digital transmission of TV channel. The use of multiple wireless standards such as IEEE 802.11a, IEEE 802.22, IEEE 802.19.1 and many more wireless networks operating in the same frequency band of TVWS creates the coexistence scenario which involves the heterogeneous networks. The interference mitigation is the most important issue in such heterogeneous networks. In literature, the issue of interference mitigation is addressed mainly at the medium access layer; however, very limited work is presented at physical layer. In this paper, an interference mitigation problem of heterogeneous cognitive radio network at physical layer is addressed. The spatial diversity based techniques are proposed to mitigate the interference in heterogeneous CRN. The coexistence of different wireless networks in secondary CRN is considered for analysis. The characterization of aggregate interference is carried out for different interference scenarios. The proposed system outperform for heterogeneous CRN network over TVWS network.
... which ensures that the signal power is purely real-valued [14]. I.e., the receive power is invariant w.r.t. the absolute phase of the beamformers: ...
... Under such a constrained environment, the SUs have two conflicting targets of maximizing their throughput and limiting the interference at the PUs. However, SUs can achieve significant throughput by exploiting the resources, such as spatial dimensions, efficiently [28]. ...
With the increasing number of wireless communication systems and the demand for bandwidth, the wireless medium has become a congested and contested environment. Operating under such an environment brings several challenges, especially for military communication systems, which need to guarantee reliable communication while avoiding interfering with other friendly or neutral systems and denying the enemy systems of service. In this work, we investigate a novel application of Rate-Splitting Multiple Access(RSMA) for joint communications and jamming with a Multi-Carrier(MC) waveform in a multiantenna Cognitive Radio(CR) system. RSMA is a robust multiple access scheme for downlink multi-antenna wireless networks. RSMA relies on multi-antenna Rate-Splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at the receivers. Our aim is to simultaneously communicate with Secondary Users(SUs) and jam Adversarial Users(AUs) to disrupt their communications while limiting the interference to Primary Users(PUs) in a setting where all users perform broadband communications by MC waveforms in their respective networks. We consider the practical setting of imperfect CSI at transmitter(CSIT) for the SUs and PUs, and statistical CSIT for AUs. We formulate a problem to obtain optimal precoders which maximize the mutual information under interference and jamming power constraints. We propose an Alternating Optimization-Alternating Direction Method of Multipliers(AOADMM) based algorithm for solving the resulting non-convex problem. We perform an analysis based on Karush-Kuhn-Tucker conditions to determine the optimal jamming and interference power thresholds that guarantee the feasibility of problem and propose a practical algorithm to calculate the interference power threshold. By simulations, we show that RSMA achieves a higher sum-rate than Space Division Multiple Access(SDMA).
... The power allocation for MIMO cognitive networks is studied in [4][5][6]. The OSA technology is analyzed in more detail in [7][8]. It means in practice a dense net of the spectrum sensing modules and the associated traffic routers should be introduced. ...
... In [22], optimization of the duration of the spectrum sensing to increase the efficiency of the cognitive nodes along with the achievement of the desired detection likelihood has been done by the authors. For enhanced output, cooperative based sensing of spectrum could be utilized [23][24][25][26][27][28][29][30]. The process of cooperative based sensing of spectrum operates as given below. ...
The cognitive radio (CR) prototype that has been intended to scheme the future wireless communication structures is emerging progressively by utilizing its various features within the existing wireless system models. A considerable quantity of research attempts has been carried out for resolving CR disputes, and numerous technologies associated with CR in addition to vibrant accessibility of the spectrum have also been incorporated. Furthermore, software-defined radio [SDR] systems have progressed to a larger extent, where it can be utilized for implementing the CR networks. This paper is intended to provide wide-ranging investigation for deploying the increasing exploration in the field of CR systems by including all features like spectrum sensing, evaluations, numerical designing of spectrum utilization and concepts of physical layer including the modulation scheme, multiple access techniques, resource distribution, cognitive learning and strength and safety measures in CR networks. The evolving developments of CR research and disputes associated to the cost-effective CR systems are also summarized in this research study.
... It is worth noting that the investigated uplink-and-downlink spectrum sharing between NPNs and public networks is different from the conventional spectrum sharing in cognitive radio (see, e.g., [7]- [9]). In conventional cognitive radio, cognitive users try to access the licensed spectrum of the primary systems that generally belong to a different entity; in this case, the primary systems are normally not aware of the existence of cognitive systems and thus cannot cooperate in helping the cognitive transmission. ...
Different from public 4G/5G networks that are dominated by downlink traffic, emerging 5G non-public networks (NPNs) need to support significant uplink traffic to enable emerging applications such as industrial Internet of things (IIoT). The uplink-and-downlink spectrum sharing is becoming a viable solution to enhance the uplink throughput of NPNs, which allows the NPNs to perform the uplink transmission over the time-frequency resources configured for downlink transmission in coexisting public networks. To deal with the severe interference from the downlink public base station (BS) transmitter to the coexisting uplink non-public BS receiver, we propose an adaptive asymmetric successive interference cancellation (SIC) approach, in which the non-public BS receiver is enabled to have the capability of decoding the downlink signals transmitted from the public BS and successively cancelling them for interference mitigation. In particular, this paper studies a basic uplink-and-downlink spectrum sharing scenario when an uplink non-public BS and a downlink public BS coexist in the same area, each communicating with multiple users via orthogonal frequency-division multiple access (OFDMA). Under this setup, we aim to maximize the common uplink throughput of all non-public users, under the condition that the downlink throughput of each public user is above a certain threshold. The decision variables include the subcarrier allocation and user scheduling for both non-public (uplink) and public (downlink) BSs, the decoding mode of the non-public BS over each subcarrier (i.e., with or without SIC), as well as the rate and power control over subcarriers. Numerical results show that the proposed adaptive asymmetric SIC design significantly improves the common uplink throughput as compared to benchmark schemes without such design.
... As the wireless standards move from the recent initial deployment of fifth-generation (5G) new radio (NR) to 6G, there is an urgency in transcending the current data rates, robustness, spectral reuse, latency, and energy efficiency. Nearly all recent wireless technologies employ multiple antennas to address these challenges [1]. For example, the spatial diversity provided by the use of multiple antennas is helpful in multipath scenarios. ...
Cognitive communications have emerged as a promising solution to enhance, adapt, and invent new tools and capabilities that transcend conventional wireless networks. Deep learning (DL) is critical in enabling essential features of cognitive systems because of its fast prediction performance, adaptive behavior, and model-free structure. These features are especially significant for multi-antenna wireless communications systems, which generate and handle massive data. Multiple antennas may provide multiplexing, diversity, or antenna gains that, respectively, improve the capacity, bit error rate, or the signal-to-interference-plus-noise ratio. In practice, multi-antenna cognitive communications encounter challenges in terms of data complexity and diversity, hardware complexity, and wireless channel dynamics. The DL-based solutions tackle these problems at the various stages of communications processing such as channel estimation, hybrid beamforming, user localization, and sparse array design. There are research opportunities to address significant design challenges arising from insufficient data coverage, learning model complexity, and data transmission overheads. This article provides synopses of various DL-based methods to impart cognitive behavior to multi-antenna wireless communications.
... To optimize secondary transmit power allocation spectrum sharing, According to [13][14][15][16][17][18] has investigates the generalized Lloyds-type algorithm (GLA) [19][20][21][22] that utilizing quantized channel state information (CSI). A modified GLA is constructed for obtaining maximal power codebook, that proven to be generally merged and factually steady. ...
To reduce the detection failure of the exchanging signal power onto the OFDM subcarrier signal at uniform quantization, dynamic subcarrier mapping is applied. Moreover, to addressing low SNR’s wall-less than pre-determine threshold, non-uniform quantization or adaptive quantization for the signal quantization size parameter is proposed. μ-law is adopted for adaptive quantization subcarrier mapping which is deployed in mobility environment, such as Doppler Effect and Rayleigh Fading propagation. In this works, sensing node received signal power then sampled into a different polarity positive and negative in μ-law quantization and divided into several segmentation levels. Each segmentation levels are divided into several sub-segment has representing one tone signal subcarrier number OFDM which has the number of quantization level and the width power. The results show that by using both methods, a significant difference is obtained around 8 dB compared to those not using the adaptive method.
... The tradeoff between throughput maximization and interference minimization for SUs is studied in [115] from an information-theoretic perspective, where the optimal transmission scheme that achieves the capacity of the secondary transmission as well as some sub-optimal algorithms is presented. In addition, precoding designs for CR networks are studied in [116]- [119] for both perfect CSI and imperfect CSI, where a precoding scheme termed MSLNR, which is a combination of the optimal minimum-mean-squared-error (MMSE) receiver and the signal-to-leakage-plus-noise ratio (SLNR) transmitter, is proposed in [116]. ...
Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area.
... where (x) + = max (x, 0), and represents the maximum tolerable average interference at PR [29], which is called the interference temperature limit. Proof For any fixed w, it can be observed that the channel capacity of the suspicious link is limited by two constraints: one is the transmit power constraint at ST; the other is the interference temperature constraint at SR. ...
Abstract In this paper, we considered a robust beamforming design problem for a proactive eavesdropping via jamming, in which a full-duplex legitimate monitor tries to eavesdrop on a suspicious communication link between the secondary pairs in an unmanned aerial vehicle (UAV)-enabled cognitive radio network. Due to the channel estimation errors, we assume that the channel state information is not perfectly known. To ensure the successful eavesdropping, jamming signals are designed to disrupt the suspicious receivers and the primary receiver at the same time, which should have the good tradeoff between those two effects. We aimed to maximize the achievable eavesdropping rate under the transmitting power constraint at the legitimate monitor and the interference temperature constraint at the primary receiver, which was formulated as a non-convex problem with infinite constraints. We firstly transform the original problem into a simplified one with finite constraints. Then, an analytical solution in significant low-complexity is proposed by decomposing the simplified problem. Numerical results are finally presented to evaluate the performance of our proposed schemes in UAV-enabled wireless communication networking.
... Recently, there has been a great deal of research related to this interesting problem. When the primary users are legacy systems that do not actively participate in transmit power control, the QoS of the primary users is maintained by introducing interference-power constraint measured at the primary receiver [1]. ...
Spectrum is becoming a valuable resource and its usage is highly increasing demand nowadays. In order to efficiently utilize the spectrum,, cognitive radio (CR) technology was introduced. Spectrum efficiency can be further improved by MIMO (Multiple Input Multiple) CRN(Cognitive Radio Network) systems. Primary and secondary users are present in CR systems. Single and multiple antennas are equipped with the primary and secondary users respectively. Here interference is the major concern when the primary and secondary users are transmitting simultaneously. To overcome the interference among the users, successive interference cancellation (SIC) method was suggested and evaluated, which is done with MATLAB software and the performance of the system is analyzed.
... On the other hand, by using multiple input multiple output (MIMO) techniques, spatial diversity or spatial multiplexing can be achieved, which leads to improving the performance of communication systems 8,9 . Therefore, CR and MIMO have been combined in order to benefit the capacity of multiple antennas 10,11,12 . An efficient way to achieve spatial multiplexing and limit interference in MIMO CR systems, is beamforming of transceiver antennas 13,14 . ...
In this paper, power allocation and beamforming are considered in a multiple input multiple output (MIMO) downlink cognitive radio (CR) communication system, which a base station (BS) serves one primary user (PU) and one secondary user (SU). In order to design the CR system, a constrained multiobjective optimization problem is presented. Two objectives are the signal to noise plus interference ratios (SINRs) of PU and SU. Since PU has a spectrum license for data communication, a constraint in the optimization problem is that the SINR of PU must be greater than a predefined threshold based on the PU demand requirement. Another constraint is a limitation on power in BS. By considering the mentioned model, three iterative algorithms are proposed. At each iteration of all algorithms, the receiver beamforming vectors are derived based on the maximization of PU and SU SINRs, by assuming that the allocated powers and BS beamforming vectors are known. Also, power is assigned to users such that the constraint of power limitation is satisfied. The difference between the algorithms is in the obtaining of transmitter beamforming parameters. We evaluate the performance of the proposed algorithms in terms of bit error rate (BER) in simulations. Also, the computational complexity of the proposed algorithms is obtained. In this paper, power allocation and beamforming are considered in a multiple input multiple output (MIMO) downlink cognitive radio (CR) communication system, which a based station (BS), serve one primary user(PU) and one secondary user(SU). In order to design the CR system, a constrained multi‐object optimization problem is presented. Two objectives are the signal to noise plus interference ratio (SINR)s of PU and SU. By considering the mentioned model, three iterative algorithms are proposed.
... Generally speaking, multiple antennas can provide the SU-Tx in an CSA system more degrees of freedom in space, which can be split between the signal transmission to maximize the secondary transmit rate and the interference avoidance for the PUs. In [19], the multiple-input multiple-output (MIMO) channel capacity of the SU in a multi-antenna CSA system has been investigated. It shows that the primary protection constraint makes the methods proposed for the traditional MIMO system inapplicable for the CR transmit and receive design. ...
Concurrent spectrum access (CSA), which allows different communication systems simultaneously transmit on the same frequency band, has been recognized as one of the most important techniques to realize the dynamic spectrum management (DSM). By regulating the interference to be received by primary users, the secondary users are able to gain continuous transmission opportunity. Without the need of frequent spectrum detection and reconfiguration, the CSA has the merit of low cost and easy implementation in practice. In this chapter, we will present some important CSA models, discuss the key problems existing in these CSA systems, and review the techniques to deal with these problems.
Covert transmission is studied for an intelligent reflecting surface (IRS) aided communication system, where Alice aims to transmit messages to Bob without being detected by the warden Willie. Specifically, an IRS is used to increase the data rate at Bob under a covert constraint. For the considered model, when Alice is equipped with a single antenna, the transmission power at Alice and phase shift at the IRS are jointly optimized to maximize the covert transmission rate with either instantaneous or partial channel state information (CSI) of Willie’s link. In addition, when multiple antennas are deployed at Alice, we formulate a joint transmit beamforming and IRS phase shift optimization problem to maximize the covert transmission rate. One local optimal algorithm and two low-complexity suboptimal algorithms are proposed to solve the problem. Furthermore, for the case of imperfect CSI of Willie’s link, the optimization problem is reformulated by using the triangle and Cauchy-Schwarz inequalities. The reformulated optimization problems are solved using an alterative algorithm, semidefinite relaxation (SDR) and Gaussian randomization techniques. Finally, simulations are performed to verify our analysis. The numerical results show that an IRS can degrade the covert transmission rate when Willie is closer to the IRS than Bob.
Cloud computing is used by the mass community. Categories of users using cloud resources are indifferent. Cloud security is thus the area of concern. This paper focuses on the security aspect by modifying the BDNA procedure. Although DNA-based encryption is considered one of the safest mechanisms for managing data within the cloud, it has a flaw of a Key Clash that is rectified using a random number generator and hashing mechanism within BDNA. The impingement occurs when the key generated with DNA has the same location as the earlier key location. The employed mechanism is termed as chain-based BDNA to improve security further also with impingement handling. It considered chaining-based BDNA and BDNA approach to tackling the problem of impingement with keys. The parameters considered are execution time in key formation, reliability, number of impingements. BDNA is based on binary encryption and to enhance the security further, excess three codes are merged within the proposed mechanism. The proposed system is implemented using Netbeans8.1 java-based platform along with cloudsim4.0. The overall result of encryption is least as time consumption is reduced and highest in terms of reliability as compared to the BDNA approach.
Face images have close correlation and redundant information, by making the recognition system inefficient and increasing the complexity of the classifier. High information repetition and relationships to confront pictures result in wasteful aspects when such pictures are explicitly utilized for recognition. To reduce information redundancy we used DCT, which preserves only pertinent information of face, and complexity of classifier reduced as the length of feature vector gets reduced and normalization of a feature vector to increase the robustness of the system. Here in this work, a hybrid method of face recognition is presented in which a feature vector constructed using DCT provided to artificial neural networks. For classification, the multilayer perception (MLP) is used by an artificial neural network with a backpropagation algorithm. The recognition rate increased and the result was tested on a benchmark dataset.
Bu çalışmada, cihazdan cihaza (D2D) haberleşme çiftleri arasında, hücresel kullanıcılar arasında ve D2D çifti ile hücresel kullanıcılar arasında oluşan girişim problemlerini gidermeyi amaçlayan, iki farklı sistem modeli analiz edilmektedir. İlk incelenen sistem modeli, eşit güç kontrolü ve kısıtlamalar kullanılarak gerçeklenen parçacık sürü optimizasyonu (PSO) tabanlı kaynak tahsisi ve mod seçimidir. Bu yöntemle mevcut alt kanalların verimli ve optimal şekilde kullanılması, en yüksek seviyeli toplam kullanıcı hızının elde edilmesi sağlanmaktadır. İlave olarak, kullanıcı sayısı, yol kaybı üssü, yol kaybı değeri, iterasyon sayısı, alt kanal sayısı gibi toplam kullanıcı hızını etkileyen faktörler de değerlendirilmektedir. Analiz edilen diğer sistem modelinde, hücresel kullanıcıların D2D kullanıcı çiftine oluşturdukları girişim için bir eşik seviyesi belirlenmektedir. Eşik seviyesi değeri ile oluşturulan girişim sınırlı alan için üzerinde çalışılan ikinci sistem modeli ile girişim azaltma ve toplam kullanıcı hızını, kaynak tahsisi ve mod seçimi yöntemine göre yükseltme başarımı sağlanmaktadır. Her iki sistem modeli için, hücresel kullanıcı sayısı temel alınarak, toplam kullanıcı hızları karşılaştırılmaktadır. Karşılaştırma sonucunda girişim sınırlı alan sistem modelinin girişim gideriminde kaynak tahsisi ve mod seçimi modeline göre daha etkili olduğu görülmüştür. Girişim sınırlı alan sistem modelinde, girişim sınırlı alana hücresel kullanıcılardan bazıları dahil olmadığı için kapasite kaybına neden olmaktadır. Kaynak tahsisi ve mod seçiminde kapasite kaybı gerçekleşmemektedir.
In contrast with the traditional cryptography, physical layer security has attracted the attention of many researchers having aim at reinforcing the security of communication systems. As far as vehicular communication is concerned, it is challenging to maintain secure and reliable communication between the connected vehicles due to the density, mobility, and dynamic network topology. This paper considers a vehicle to infrastructure communication in which a legitimately fixed transmitter equipped with a single antenna transmits a confidential message to a legitimate mobile receiver equipped with multiple antennas in the presence of a passive mobile eavesdropper. In such a single input multiple output wireless system, the receiver performs the maximal ratio combining technique assuming constant vehicle speed. We assume that the antennas are closely spaced and depending upon the imperfect channel state information (CSI), we derive the closed-form expressions for the average outage probability, secrecy outage probability, and average secrecy outage rate over the uniform, exponential, and arbitrary correlated Nakagami-
${m}$
channels for dual antenna branches. In order to gain insight we also perform the high SNR asymptotic analysis of the outage probability and secrecy outage probability. Simulations are conducted to validate the accuracy of our derived analytic expressions. The computation error analysis is carried out to provide the suitability of the correlation type at the legitimate receiver side. Our findings suggest that the performance of the case with exponential channel correlation is better than those for the uniform and arbitrary. Numerical results show the joint effect of vehicle mobility and the antenna correlation on secrecy performance. Moreover, we also observed that the imperfect knowledge of the CSI degrades the security of the confidential messages severely under the effect of mobility.
Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs). Meanwhile, intelligent reflecting surface (IRS), also known as reconfigurable intelligent surface (RIS), has been recently proposed as a promising approach to enhance energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. To improve both SE and EE, in this paper, we introduce multiple IRSs to a downlink multiple-input single-output (MISO) CR system, in which a single SU coexists with a primary network with multiple PU receivers (PU-RXs). Our design objective is to maximize the achievable rate of SU subject to a total transmit power constraint on the SU transmitter (SU-TX) and interference temperature constraints on the PU-RXs, by jointly optimizing the beamforming at SU-TX and the reflecting coefficients at each IRS. Both perfect and imperfect channel state information (CSI) cases are considered in the optimization. Numerical results demonstrate that IRS can significantly improve the achievable rate of SU under both perfect and imperfect CSI cases.
Multi-user Gaussian MIMO wiretap channel is considered under interference power constraints (IPC), in addition to the total transmit power constraint (TPC). Algorithms for
global
maximization of its secrecy rate are proposed. Their convergence to the secrecy capacity is rigorously proved and a number of properties are established analytically. Unlike known algorithms, the proposed ones are not limited to the MISO case and are proved to converge to a
global
rather than local optimum in the general MIMO case, even when the channel is not degraded. In practice, the convergence is fast as only a small to moderate number of Newton steps is required to achieve a high precision level. The interplay of TPC and IPC is shown to result in an unusual property when an optimal point of the max-min problem does not provide an optimal transmit covariance matrix in some (singular) cases. To address this issue, an algorithm is developed to compute an optimal transmit covariance matrix in those singular cases. It is shown that this algorithm also solves the dual (nonconvex) problems of
globally
minimizing the total transmit power subject to the secrecy and interference constraints; it provides the minimum transmit power and respective signaling strategy needed to achieve the secrecy capacity, hence allowing power savings.
In this paper we consider the signal-to-interference-and-noise ratio (SINR) optimization problem in the multi-user multi-input-single-output (MISO) uplink wireless network assisted by intelligent reflecting surface (IRS) under individual information rate constraints. We perform a comprehensive investigation on various aspects of this problem. First, under the individual rate constraints, we study its feasibility. We present a sufficient condition which guarantees arbitrary set of individual information rates. This result strengthens the feasibility condition in existing literature and is useful to the power control/energy efficiency (EE) maximization problem when IRS is present. Then, based on the penalty dual decomposition (PDD) and nonlinear equality alternative direction method of multipliers (neADMM) method, we present new algorithms to tackle the IRS configuration problems, which simultaneously involves multi-dimensional constant-modulus constraints and other additional constraints. Note that the similar hard-core problem has recurrently appeared in various research work on IRS recently. Convergence property and analytic solutions of our proposed algorithms are carefully examined. Moreover, iterative algorithms are developed to detect the feasibility and maximize the SINR. Extensive numerical results are presented to verify the effectiveness of our proposed algorithms.
This chapter focuses on the role of antenna arrays in spectrum sharing, with emphasis on the spectrum sensing and shared spectrum access areas, for which specific representative examples are provided. It summarizes the key attributes of antenna arrays, namely signal power gain, interference nulling ability, diversity gain, and spatial multiplexing gain. The antenna array attributes listed are particularly useful in enabling and/or enhancing spectrum sharing in a variety of setups within the standard paradigms. The chapter lists the key mechanisms for this by considering separately the spectrum sensing and the shared spectrum access tasks. It presents a simple resource allocation scheme for coordinated beamforming transmission in an underlay spectrum sharing setup. The chapter also presents examples of novel spectrum sensing mechanisms and evaluates their performance via over‐the‐air experiments.
This open access book, authored by a world-leading researcher in this field, describes fundamentals of dynamic spectrum management, provides a systematic overview on the enabling technologies covering cognitive radio, blockchain, and artificial intelligence, and offers valuable guidance for designing advanced wireless communications systems. This book is intended for a broad range of readers, including students and professionals in this field, as well as radio spectrum policy makers.
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