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Comparison of Underlay and Overlay Spectrum Sharing Strategies in MISO Cognitive Channels
Abstract
We consider an extension of the cognitive radio channel model in which the secondary transmitter has to obtain (“learn”) the primary message in a first phase rather than having non-causal knowledge of it. We propose an achievable rate region that combines elements of decode-and-forward relaying with coding for the pure cognitive radio channel model. Moreover, we find the choice of parameters that maximize the secondary rate under a primary rate constraint. Finally, we compare numerically the performance of our system to that of an underlay scheme that combines beamforming, rate splitting, and successive decoding. We observe that although the overlay design provides higher rates, the losses due to the first phase are quite severe. In fact, for the considered scenarios, cleverly designed underlay schemes can provide comparable performance.
... The energy-efficient transmission for hybrid spectrum sharing CR networks was investigated in Zuo et al., 11 and an optimization model was established to maximize the energy-efficiency capacity. Blasco-Serrano et al. 14 have compared the system throughput using a learning phase in a secondary network for both underlay and overlay models. A classical idea of using cluster-based spectrum sensing and access techniques under hybrid overlay/underlay CR network through optimal relay selection scheme has been proposed Rajaganapathi and Nathan. ...
... Simplifying (14) and after some manipulations, the maximal transmit power of the SU − Tx under the outage of the PUs is found as follows: ...
... This is in true sense as the behavior observed in Bao et al. 10 But as the primary transmit power increases beyond that value, there is a degradation of outage behavior at secondary receiver. The explanation of this behavior can be justified by (14) and (18) which bounds the peak transmit power of secondary transmitter. Figure 4 shows the outage probability at secondary receiver versus P p /N 0 under joint underlay/overlay protocol considering the variation of primary and secondary rates. ...
Efficient spectrum utilization is a promising technique for a prolonged unused radio frequency (RF) spectrum in a wireless network. In this paper, an adaptive spectrum sharing cognitive radio (CR) network has been proposed consisting of a primary user (PU) and secondary user transmitter (SU − Tx) that communicates with secondary user receiver (SU − Rx) via multiantenna‐based proactive decode‐and‐forward (DF) relay selection scheme. In our model, strategically an adaptable joint venture on underlay/overlay protocol is defined based on channel occupancy using spectrum sensing technique. Here, secondary transmitters (i.e., source transmitter) continuously sense the PU activities by energy detector and can simultaneously transmit to secondary receivers. Depending on sensing result secondary transmitters automatically switches in underlay mode if PU is active otherwise operates in overlay mode. The advantage of this scheme is that the joint mode of transmission allows the SUs to maximize their transmission rate. The outage performance at SU − Rx and closed‐form expressions of joint underlay/overlay protocol has been evaluated. The power control policies at different transmitter nodes are taken care of. With the same diversity order, a trade‐off between multiantenna and multirelay is shown. This comparison shows improvement in outage behavior when the count in relays surpasses the number of antennas. Finally, the analytical model of smart efficient spectrum utilization without harming license users in CR is validated by MATLAB simulation.
... The ITU proposes the segregation of the band in a recommendation [4], which is of course not spectrum efficient. A more intelligent approach is to use Cognitive Radio (CR) paradigm [5]. This paradigm may be implemented into three different approaches: (i) the overlay approach which, as a drawback, requires exchanges between satellite systems and existing FS systems; (ii) the interweave approach which, as a drawback, requires the FSS users to observe their environment to predict the appropriate transmission times; and (iii) the underlay approach which requires to know the average channels between FS and FSS transmitters. ...
... We first go back to baseband, we then apply the matched filter p R (t) := p T (−t), Finally, the signal is sampled at the symbol rate, resulting in the sequence z (j,p) k,n , By assuming perfect synchronization between beams, after a straightforward computation putting Eqs. (1)(2)(3)(4)(5)(6)(7)(8) into Eq. (9), we have [3] with the following two Volterra kernels of first-order and third-order respectively, Consequently, the term z (j,p) k,n can be decomposed into four parts: ...
Cognitive satellite communication (SatCom) is rapidly emerging as a promising technology to overcome the scarcity of the exclusive licensed band model in order to fulfill the increasing demand for high data rate services. The paper addresses power allocation methods for multi-operator multi-beam uplink satellite communication systems co-existing with a Ka-band terrestrial network, using cognitive radio paradigm. Such a scenario is especially challenging because of (i) the coexisting multiple SatCom operators over the cognitive band need to coordinate the use of their resources under limited inter-operator information exchange, and (ii) nonlinear onboard high power amplifier (HPA) which leads to nonlinear interference between users and beams. In order to tackle the first challenge, we propose distributed power allocation algorithms including the standard Alternate Direction Multiplier Method (ADMM); Regarding the HPA nonlinear impairment, we propose nonlinear-aware power allocation based on Signomial Programming. The proposed solutions outperform state-of-the-art in both cases.
... This paper extends our previous work on the coexistence of a SISO primary system with a MISO secondary link for underlay [14] and overlay systems [36] to the case of coexisting MISO primary and MIMO secondary systems. The addition of multiple antennas at the primary transmitter and secondary receiver results in a model that is richer and substantially more complex. ...
... For example, if ρ = 1, the maximum advantage corresponds to a factor of approximately 2.55. In contrast, for small loads, the advantage might be too small to compensate for the additional complexity when compared to the underlay strategy; for example, in the case of a single-antenna primary system, we observed an advantage factor of just 1.15 (see [36]). Similar conclusions can be drawn for Figure 5: the maximum tends to move towards the primary transmitter as we increase the secondary power or the number of antennas and the region where overlay is better most of the time becomes larger. ...
We consider the coexistence of a multiple-input multiple-output secondary system with a multiple-input single-output primary link with different degrees of coordination between the systems. First, for the uncoordinated underlay cognitive radio scenario, we fully characterize the optimal parameters that maximize the secondary rate subject to a primary rate constraint for a transmission strategy that combines rate splitting and interference cancellation. Second, we establish a model for the coordinated overlay cognitive radio scenario that consists of a message-learning phase followed by a communication phase. We then propose a transmission strategy that combines techniques for cooperative communication and for the classical cognitive radio channel. We optimize our system to maximize the rate of communication for the secondary users under a primary-user rate constraint and find efficient algorithms to compute the optimal system parameters. Finally, we compare both cognitive radio strategies to assess their relative merits and to evaluate the effect of the message-learning phase. We observe that for closely located transmitters, the overlay strategy outperforms the underlay strategy. In this situation, learning the primary message is very beneficial for the secondary systems, especially if they are interference-limited rather than power-limited. The situation is reversed when the distance between the transmitters is large. In either case, we observe that there is room for significant improvement if the transmitter implements both strategies and decides adaptively which one to use according to the channel conditions. We conclude our work with a discussion on the extension to the coexistence with multiple-input multiple-output primaries.
... Interference-limited communications has been attracting much interest in recent years; One major reason is the emergence of nonorthogonal multiple access (NOMA) as a major paradigm for 5G communications [1]. Another important motivation is that interference-limited communications corresponds to multiple existing communications scenarios, including, for example, digital subscriber line (DSL), in which crosstalk is limiting the rate of information [2], and underlay cognitive communications, in which the secondary user is the major source of interference to the primary user [3]. ...
In this work we study the capacity of interference-limited channels with memory. These channels model non-orthogonal communications scenarios, such as the non-orthogonal multiple access (NOMA) scenario and underlay cognitive communications, in which the interference from other communications signals is much stronger than the thermal noise. Interference-limited communications is expected to become a very common scenario in future wireless communications systems, such as 5G, WiFi6, and beyond. As communications signals are inherently cyclostationary in continuous time (CT), then after sampling at the receiver, the discrete-time (DT) received signal model contains the sampled desired information signal with additive sampled CT cyclostationary noise. The sampled noise can be modeled as either a DT cyclostationary process or a DT almost-cyclostationary process, where in the latter case the resulting channel is not information-stable. In a previous work we characterized the capacity of this model for the case in which the DT noise is memoryless. In the current work we come closer to practical scenarios by modelling the resulting DT noise as a finite-memory random process. The presence of memory requires the development of a new set of tools for analyzing the capacity of channels with additive non-stationary noise which has memory. Our results show, for the first time, the relationship between memory, sampling frequency synchronization and capacity, for interference-limited communications. The insights from our work provide a link between the analog and the digital time domains, which has been missing in most previous works on capacity analysis. Thus, our results can help improving spectral efficiency and suggest optimal transceiver designs for future communications paradigms.
... Dans cette thèse, les utilisateurs primaires sont le réseau terrestre en place (appelé FS) et les utilisateurs secondaires sont les terminaux satellitaires, appelés The aim of this thesis is to focus on the satellite uplink in order to provide new solutions for extending the data rate by using additional non-exclusive 2 GHz bandwidth in 28 GHz, and consequently opening new areas of applications and services in satellite communications on frequencies already used by terrestrial systems. This goal leads to the proposed resource allocation techniques for an underlay satellite cognitive systems [1]. Indeed, the initial studies of the European Project CoRaSat showed that the cognitive underlay paradigm suits well for deployment of cognitive satellite terminals in uplink [2,3]. ...
This thesis addresses the problem of resource allocation for cognitive satellite communications.In a context of increasing throughput demands, satellite communication systems are required to use frequencies already used by terrestrial systems. The underlay cognitive radio paradigm allows a secondary network to use the same frequency band that a primary network uses. However, the interference created by the secondary network must not exceed a certain limit, which is set by the primary network.We consider a cognitive satellite communication system, where terrestrial users transmit information to a satellite, and that satellite sends it back to a terrestrial gateway in a relay-like fashion.In this way, the terrestrial users of the satellite secondary network generate interference on the primary network, which is due to the secondary lobes of the transmitting antennas. The management of the transmission power of the secondary satellite users becomes essential to limit the interference on the primary terrestrial network and, at the same time, to reach the maximum throughput of the system. Moreover, taking into account the nonlinearities coming from the satellite, especially the high-power amplifier, becomes crucial when the satellite is used at its maximum capabilities.This is because the non-linear effects produced by the amplifier, modeled by Volterra series, degrade the system throughput.In this context, the thesis consists in proposing resource allocation algorithms in order to optimize the sum-rate of the satellite system, while respecting the interference limits set by the primary terrestrial network, taking into account the nonlinear effects generated by the satellite components.
... In addition to this, the authors have assessed the system performance in terms of outage probability, symbol error rate, and outage capacity over the Nakagamim fading environment by deriving the respective analytical expressions and demonstrated that the hybrid approach outperforms over the conventional underlay scheme. A comparison of interweave and underlay CU transmission is presented in [42] and it is depicted that due to the overhearing nature of cognitive transmitters, i.e. learning phase, the performance of interweave approach degrades. In addition to this, the use of interference decoding methods in the underlay system can approach the performance of interweave system. ...
The underlay spectrum access is a very prominent technique in cognitive radio (CR) communication systems in which the primary users (PUs) share the spectrum with the cognitive users (CUs), simultaneously. However, the PU communication is protected by constraining the CUs' transmission power in such a way that the interference power introduced at the PU receiver is under the tolerable limits. In this comprehensive survey, we have presented the general framework of CR communication technology and emphasized on the spectrum accessing and sharing techniques. Various approaches of the optimal power allocation to CUs, namely, the game theory, price auction, convex optimization and iterative water-filling are presented. Moreover, to address the random nature of channel, the performance metrics analysis with the perfect and imperfect channel state information is also illustrated. Finally, the potential issues and research challenges for power management in the CR communication systems are presented which need to be explored.
... transmission power and operating frequency) [17]. The CR network has three paradigms for the spectrum access interweave, overlay, and underlay [18,19]. The interweave scenario is that the cognitive users (CUs) sense the spectrum in three dimensions (e.g. ...
In a multiple‐input multiple‐output (MIMO) cognitive radio network, the cognitive users (CUs) coexist with the primary users (PUs) in the same spectrum for boosting the spectrum efficiency. Based on the informed limit of the interference power from the PUs, the CUs' compete to minimise the total interference power generated. In this study, noncooperative and cooperative game theoretic approaches are derived for network interference management (NIM). In the first scenario, the NIM problem computes the sum of minimum individual CU's interference power produced on the PU to converge to equilibrium by using the best response iteration method. The second one, NIM estimates Nash product to converge to Nash bargaining solution by using the dual decomposition method. Numerical results prove the effectiveness of the cooperative scenario that minimises the network interference power. Two new metrics are proposed to evaluate the performance in these scenarios. The interference cooperative loss metric estimates the overall network interference power loss from CUs cooperation rather than non‐cooperation in the game theoretic solution. Capacity cooperative gain metric estimates the overall network capacity gain from CUs cooperation rather than non‐cooperation in the game theoretic solution for a fixed acceptable interference level.
... In this case, the CSUs must sense the underutilized spectrum of the FBS to find an appropriate channel and then perform VHO on that channel. Once a PU requests the same channel, the CSU should leave that channel, perform spectrum handover (SHO), and switch to another appropriate free channel [26]. A management strategy is then necessary to control the number of SHOs, decrease the number of unnecessary handovers, and minimize the effect of multiple interruptions [27][28][29][30]. ...
The limitation of the radio spectrum and the rapid growth of communication applications make optimal usage of radio resources essential. Cognitive radio (CR) is an attractive research area for 4G/5G wireless communication systems, which enables unlicensed users to access the spectrum. Delivering higher spectral efficiency, supporting the higher number of users, and achieving higher coverage and throughput are the main advantages of CR-based networks compared to conventional ones. The main goal of this book is to provide highlights of current research topics in the field of CR-based systems. The book consists of six chapters in three sections focusing on primary and secondary users, spectrum sensing, spectrum sharing, CR-based IoT, emulation attack, and interference alignment.
... In this case, the CSUs must sense the underutilized spectrum of the FBS to find an appropriate channel and then perform VHO on that channel. Once a PU requests the same channel, the CSU should leave that channel, perform spectrum handover (SHO), and switch to another appropriate free channel [26]. A management strategy is then necessary to control the number of SHOs, decrease the number of unnecessary handovers, and minimize the effect of multiple interruptions [27][28][29][30]. ...
... • The overlay approach assumes that the secondary user has a-priori knowledge about the transmission parameters of the primary user. Hence, the secondary can transmit at a maximal power level, but at the same time relay some of the primary messages to maximize the signal-to-noise ratio at the primary receiver [31]. Although it is a cooperative sharing, this method introduces additional overhead for the secondaries and security threats for the primaries. ...
Radio frequencies, as currently allocated, are statically managed. Spectrum sharing between commercial users and incumbent users in the Federal bands has been considered by regulators, industry, and academia as a great way to enhance productivity and effectiveness in spectrum use. However, allowing secondary users to share frequency bands with sensitive government incumbent users creates new privacy threats in the form of inference attacks. Therefore, the aim of this thesis is to enhance the privacy of the incumbent while allowing secondary access to the spectrum. First, we present a brief description of different sharing regulations and privacy requirements in Federal bands. We also survey the privacy-preserving techniques (i.e., obfuscation) proposed in data mining and publishing to thwart inference attacks. Next, we propose and implement our approach to protect the operational frequency and location of the incumbent operations from inferences. We follow with research on frequency protection using inherent and explicit obfuscation to preserve the incumbent's privacy. Then, we address location protection using trust as the main countermeasure to identify and mitigate an inference risk. Finally, we present a risk-based framework that integrates our work and accommodates other privacy-preserving approaches. This work is supported with models, simulations and results that showcase our work and quantify the importance of evaluating privacy-preserving techniques and analyzing the trade-off between privacy protection and spectrum efficiency
... To achieve this goal, the concept of CR has emerged. Different CR strategies have been defined [4,5] by taking into account how the secondary terminals uses the spectrum. Among them, we have the interweave strategy, where the secondary users use the spectrum holes, left by the primary, to transmit their information. ...
Small-cells are considered as an effective solution to increase capacity and offload traffic from, the current macro-cell cellular system. Owing to the difficulty and costs involved in acquiring new spectrum licenses, small-cells are expected to coexist with their respective macro-cells, in the same spectrum. This leads to considerable interference between the two systems. Optimum performance, at the macro-cell, is achieved when the small-cell terminals transmit their information over the null-space of the macro-cell link. However, availability, at the small-cell terminals, of the macro-cell channel null-space information requires full-cooperation and thus a high overhead of information exchange. In this study, the cognitive precoding schemes are designed under a limited inter-system information exchange and the constraint that the performance of the macro-cell link is kept close to the case where no small-cell network does exist. Two techniques are considered: a two-bit quantisation precoded and a dual space-frequency coding precoded approach. It is demonstrated that the first achieves a performance close to the full cooperation approach recently proposed, but with very low information exchange requirements. For the second, it is show that both the systems are able to coexist without any inter-system cooperation and with a performance close to the non-coexistence scenario.
The real world deals with the process of advancement of the sharing of uniform spectrum by both 4G LTE and 5G NR. This uniform spectrum gives rise to the problem of interference. Hence the process of cognition is utilized for minimizing the interference and improves the spectral efficiency. The Dynamic Spectrum Sharing (DSS) is the applicable technique for decreasing interference. Due to the same spectrum sharing made by both 4G LTE and 5G NR, there will be the origin of the problem of interference which gives challenges for various innovations in future. The problem of interference creates the minimization of reliability. For minimizing the interference, the oscillator frequency is kept stable whereas the range of oscillator frequencies for 5G NR has maximum and minimum value. The analysis specifies that for same or approximate value of frequencies for both 4G LTE and 5G NR, the reliability of the signal becomes negligible. Here the BER, BLER of the signal is maximum and the value of throughput of the signal is 0. For the purpose of maximizing the reliability and throughput, the oscillator frequencies for 5G NR is varying from maximum value to minimum value. It has been realized that if the frequency difference between 4G LTE and 5G NR is very high, then the reliability and throughput of the signal becomes maximum safeties.
In this work we study the capacity of interference-limited channels with memory. These channels model non-orthogonal communications scenarios, such as the non-orthogonal multiple access (NOMA) scenario and underlay cognitive communications, in which the interference from other communications signals is much stronger than the thermal noise. Interference-limited communications is expected to become a very common scenario in future wireless communications systems, such as 5G, WiFi6, and beyond. As communications signals are inherently cyclostationary in continuous time (CT), then after sampling at the receiver, the discrete-time (DT) received signal model contains the sampled desired information signal with additive sampled CT cyclostationary noise. The sampled noise can be modeled as either a DT cyclostationary process or a DT almost-cyclostationary process, where in the latter case the resulting channel is not information-stable. In a previous work we characterized the capacity of this model for the case in which the DT noise is memoryless. In the current work we come closer to practical scenarios by modelling the resulting DT noise as a finite-memory random process. The presence of memory requires the development of a new set of tools for analyzing the capacity of channels with additive non-stationary noise which has memory. Our results show, for the first time, the relationship between memory, sampling frequency synchronization and capacity, for interference-limited communications. The insights from our work provide a link between the analog and the digital time domains, which has been missing in most previous works on capacity analysis. Thus, our results can help improving spectral efficiency and suggest optimal transceiver designs for future communications paradigms.
A novel structure of microstrip patch antenna is presented for high gain enhancement and broadband wireless applications. The manuscript describes a comparative analysis of the patch antenna with the multiple split-ring resonators loaded patch antenna. The design performance was examined using different parameters like return loss, frequency resonance, voltage standing wave ratio, gain, and directivity. Gain enhancement is possible by enabling diffracted ground in the ground layer. The metamaterial behavior of the antenna is observed by a negative refractive index for complementary split-ring resonators (CSRR) structure. The coaxial feed is given to the antenna for excitation. The proposed design provides the return loss of −29 dB, voltage standing wave ratio (VSWR) of 1.08, and total gain of 8.34 dB. Results are authenticated by physical designing of the antenna and measuring results using a vector network analyzer. The proposed antenna structure will be used for a satellite TV network, weather radar station, Terrestrial microwave links under C band applications.KeywordsGainMetamaterialComplimentary split-ring resonatorMicrostrip patch antenna
In the presented paper, we propose a joint underlay/overlay cognitive radio (CR) network model assisted by adaptive hybrid relays (AHR) which are incorporated with multiple antennas. According to our proposed model, out of all primary users (PUs) band if certain number of PU bands are sensed empty, then overlay mode is used and if the PUs are communicating, then underlay mode is used. The source and relays are equipped with adaptive dual power switches, i.e., underlay and overlay mode power is selected on the basis of sensing the activity of primary users. The outage probability is calculated at the selection combined (SC)-based secondary destination. The outage performance of the system model under consideration is compared for varying number of underlay and overlay PUs. AF (amplify and forward relay), DF (decode and forward) and AHR forwarding protocols have been compared on the basis of outage performance. The influence of increasing number of relays on the overall system outage is also shown. The mathematical equation of the outage probability in different protocol has been shown in this paper.KeywordsPrimary usersSecondary usersUnderlay CROverlay CRAdaptive hybrid relaySelection combining
Due to the random spectrum sensing of channels in cognitive radio networks, the probability of channel to be sensed active is significantly high, resulting in high data loss due to which the effective throughput of the network decreases significantly. In this chapter, the challenging issues regarding the selection of channel for spectrum sensing after spectrum prediction are exploited to enhance the throughput of cognitive user (CU). First, the chapter illustrates the system model for the proposed approach. The expressions of throughput are then presented. Next, the chapter discusses the simulation results and finally discusses the future scope. A new approach for additional enhancement in the throughput of CU by exploiting the underlay communication in the spectrum sensing and prediction phases is presented and the results are compared with pre‐obtained results of Approach‐1. The results are evidence for the significant improvement in the throughput by using this approach.
Spectrum leasing has been widely regarded as one
of the most effective ways to improve the utilization of limited
spectrum resources. In this paper, we propose a novel trafficadaptive
spectrum leasing (TASL) scheme by allowing secondary
users (SUs) to lease part of licensed spectrum channels from
primary users (PUs) temporarily for transmitting the dynamically
generated secondary packets. As the time length of each
leasing period is variable according to the dynamic generation
of secondary packets, the proposed TASL can effectively satisfy
the quality-of-service (QoS) requirement of SUs and also benefit
PUs with the financial payoff provided by SUs. By establishing
a three-dimensional continuous Markov chain for the proposed
TASL, we formulate the average utilities of PUs and SUs in
terms of the expected buffering time of primary and secondary
packets as well as the expected transmission throughput of PUs
and SUs. Moreover, to coordinate the interests of PUs and SUs in
a non-cooperative manner, we also propose a Stackelberg game
model for PUs and SUs to negotiate various spectrum leasing
parameters and further apply two specific rules to guarantee the
existence of a unique equilibrium solution. Numerical simulation
shows that, compared with those existing spectrum leasing
schemes that preset a fixed time length for leasing periods, the
proposed TASL can effectively improve the utilization of the
leased channels, increase the average utilities of both PUs and
SUs, and be more suitable for newly emerging applications that
are sensitive to packet transmission delay and buffering overhead.
Cognitive radio heterogeneous network (CR-HetNet) is an emerging technology which aims at enhancing the spectrum utilization through spectrum sharing among macro base station (MBS) and femto base station (FBS). Similar to other cognitive radio (CR) networks, in CR-HetNets providing the desired quality of service (QoS) for the licensed primary users (PUs) is of utmost importance. Due to the shared spectrum between PUs and cognitive secondary users (CSUs) as well as offloading policies, the spectrum handover (SHO) process must be carefully designed. Using the idea of reserved channels, this paper proposes two traffic-aware SHO schemes for cognitive HetNets. In the proposed schemes, each CSU can adopt either a shared-to-reserved (SR) or reserved-to-shared (RS) SHO strategies. The proposed approaches can be implemented in both distributed and centralized manners to maintain a tradeoff between the performance and complexity. The performance of the proposed schemes are mathematically analyzed and closed-form expressions are derived for blocking probability of the PUs and forced termination probability of the CSUs. Numerical results show that the proposed schemes outperform the existing SHO approaches, such as always-change, always-stay, and proactive methods, specifically at higher arrival rates of PUs. Moreover, several evaluation metrics, such as effective throughput, energy efficiency, and a proposed combinational utility function are investigated for both distributed and centralized schemes. The results show that the proposed centralized schemes offer higher performance compared to the distributed ones.
Spectral-efficiency and energy-efficiency are the key concerns for next-generation wireless networks. RF energy-harvesting is emerged as a prominent technology which self-empowers wireless nodes to achieve energy-efficiency. For spectral-efficiency, the opportunistic spectrum-access technology (by employing cognitive radios) is an optimal solution. Therefore, in this paper, we merge both technologies (cognitive radio & RF energy harvesting) together to achieve network-wide spectral and energy efficiency. A novel two-level residual-energy and channel-quality (capacity and idle-time) aware node-classification scheme is introduced for cluster-based cognitive radio sensor networks to select the best sensor nodes for reporting process. At first level, the nodes are classified as harvesting or transmitting nodes based on their residual energy. Later on, the best node-channel pairs are formed for transmitting nodes using Hungarian algorithm. In the second level of classification, only those nodes are selected for reporting, which can transmit reporting packet in the given duration on the allocated channel. Otherwise, the node is directed to perform energy harvesting task to achieve energy-balancing and avoid unsuccessful reporting. Simulation results demonstrate that the proposed scheme shows better performance gain in terms of successful reporting rate compared to existing node-classification schemes. Furthermore, we compare the proposed node-channel pairing scheme with greedy-pairing and random-pairing schemes and illustrate the performance gain in terms of successful reporting.
In this paper, we consider an extension of the cognitive radio channel model in which the secondary transmitter has to obtain (learn) the primary message rather than having non-causal knowledge of it. We formulate an achievable rate region that combines elements of compress-and-forward relaying with coding for the pure cognitive radio channel model. Moreover, we provide parameters design that maximizes the secondary rate without affecting the primary rate in the Rician channel with partial channel state information at the transmitter (CSIT). Simulation results demonstrate that the proposed compress-and-forward based strategy achieves good performance.
A power allocation strategy is proposed for single-antenna overlay cognitive radio networks, in which the secondary user helps transmit the signal of the primary user while concurrently conveying its own signal by means of a superposition coding technique. The study commences by deriving analytical expressions for the bit error rates (BERs) of the primary and secondary users. A power allocation strategy is then proposed for minimizing the total power consumption of the two users while simultaneously satisfying their respective BER constraints. The analytical BER formulas are not convex, and hence the optimization process presents a significant challenge. Accordingly, two more tractable BER approximations for the primary and secondary users are proposed to transfer the non-convex problem into a convex one. The simulation results confirm the effectiveness of the proposed power allocation strategy under various channel environments.
In view of the issue that the single-signal signal-to-noise ratio (SNR) estimation methods are unsuitable for time-frequency overlapped signals in underlay cognitive radio (CR), a novel SNR estimation method for time-frequency overlapped signals is proposed under low SNR conditions. In this method, the SNR estimation is transformed into normalized power estimation of every signal component through establishing the kurtosis of received signals on the basis of second moments and forth-order moments. The Cramer Rao Bound (CRB) of SNR estimation for time-frequency overlapped signals is also derived in this letter. Simulation results are provided to confirm that the proposed method can estimate the SNR of time-frequency overlapped signals effectively in low SNR regions.
In this paper, we propose cognitive overlay transceiver designs, where a primary transceiver pair and a secondary transceiver pair coexist in a network, and the primary user (PU) allows the secondary user (SU) to concurrently transmit its signals at the price of reducing the power of the PU's signal relayed by cooperative amplify-and-forward (AF). Since the considered transceiver design is mainly to devise the precoders both for the PU and the SU at the secondary transmitter (ST), the channel state information (CSI) has to be known at the ST. We therefore consider the limited feedback scheme with random vector quantization (RVQ), where the ST can only know the quantized channel direction information (CDI). Considering the statistics of the CSI quantization error and the linear minimum mean square error (LMMSE) receiver, we derive the closed-form MSE expressions corresponding to the PU and the SU. With the derived MSEs, we propose two robust design criteria. One criterion is to minimize the ST's power consumption under the constraint that the PU's and SU's quality-of-service (QoS; i.e., MSE) can be met. The other criterion is to minimize the SU's MSE when the PU's QoS can be controlled under a certain value and the ST satisfies the limitation of its transmission power consumption. Both the optimization problems of the proposed design criteria are not convex, and the corresponding solutions cannot be directly obtained. We then propose transfering the original optimization problems into two subproblems, where each of them is eventually formulated as a convex optimization problem, and the solutions are iteratively obtained, which is effective. Thus, the results can be obtained with the interior-point method. Simulations certify the robustness of our designs.
The coexistence of a single-input single-output (SISO) primary link and a multiple-input single-output (MISO) secondary link is considered in an extended cognitive radio channel setup, where the secondary transmitter has to obtain (“learn”) the primary message in a first phase rather than having non-causal knowledge of it. An achievable rate region is derived that combines decode-and-forward relaying with linear precoding in the second phase. The optimal transmission strategy is found that maximizes the secondary rate with the primary rate requirement. The performance of the proposed strategy is compared, where dirty-paper coding (DPC) is deployed in the second phase, in terms of average secondary rate. The performance degradation is negligible at certain SNR and primary link load, and the implementation is of lower complexity. The comparison with the underlay strategy is also performed, where the secondary transmitter has no knowledge of the primary message.
In order to achieve better statistical Quality-of-Service (QoS) provisioning for cognitive radio networks (CRN), in this paper, we develop a hybrid underlay/overlay transmission mode for CRNs. Specifically, by applying the theory of effective capacity and taking PN's activity statistics into consideration, we first analyze the maximum achievable throughput of the CRN under two dominant transmission modes, namely underlay and overlay, respectively, and provide efficient algorithms to derive optimal transmission strategies for the two modes. Following the analyses, we then propose a hybrid underlay/overlay transmission mode, through which the cognitive users' QoS requirements can be better guaranteed and network throughput can be further improved. Moreover, we analyze the optimal transmission strategies for both underlay and overlay modes under two limiting cases. Analyses indicate that 1) for the loose QoS requirement, optimal transmission strategies for both underlay and overlay modes become the water-filling algorithm; and 2) for the stringent QoS requirement, the cognitive user will transmit with constant rate. Furthermore, the impact of imperfect channel estimations on our proposed transmission mode is discussed. Simulation results are provided to demonstrate the impacts of delay QoS requirements and PN's activity statistics on maximizing the delay-constrained throughput for both underlay and overlay modes and verify the effectiveness of our proposed transmission mode. Moreover, for the overlay mode, we observe that 1) a unique optimal sensing time exists under the given QoS constraint; and 2) the optimal sensing time surprisingly increases as the QoS constraint gets more stringent.
We propose a two-phase protocol based on cooperative decode-and-forward relaying for a secondary system to achieve spectrum access along with a primary system. The primary and secondary systems comprise of a transmitter-receiver pair, PT-PR and ST-SR, respectively. In the first transmission phase, PT transmits the primary signal to PR, which is also received by ST and SR, where it is decoded. At ST, the primary signal is regenerated and linearly combined with the secondary signal by assigning fractions alpha and (1 - alpha) of the available power to the primary and secondary signals respectively. This combined signal is then broadcasted by ST in the second transmission phase. We show that as long as ST is located within a critical radius from PT, there exists a threshold value for alpha above which the outage probability of the primary system will be equal to or lower than the case without spectrum sharing. We also determine the outage probability achieved by the secondary system. Theoretical and simulation results confirm the efficiency of the proposed spectrum sharing scheme.
Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks, and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well as a priori rules about spectrum usage, cognitive radio systems seek to underlay, overlay, or interweave the cognitive radios' signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information-theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today's crowded spectrum.
This paper addresses user coexistence in cognitive radio systems by taking advantage of opportunities that arise during ARQ retransmission. It is shown that if these opportunities are properly exploited, nontrivial rates can be made available to a secondary (cognitive) pair while impinging little or no interference on the primary pair. This can be accomplished with an oblivious primary system and without assuming any non-causal information at the secondary about the primary data. Several protocols are devised that work with varying amounts of channel state information about the cognitive and primary links. The protocols are further extended to the scenario where multiple cognitive receivers exist. Performance analysis of the protocols is presented and their effectiveness is verified via simulations.
This article provides an overview of the state-of-art results on communication resource allocation over space, time, and frequency for emerging cognitive radio (CR) wireless networks. Focusing on the interference-power/interference-temperature (IT) constraint approach for CRs to protect primary radio transmissions, many new and challenging problems regarding the design of CR systems are formulated, and some of the corresponding solutions are shown to be obtainable by restructuring some classic results known for traditional (non-CR) wireless networks. It is demonstrated that convex optimization plays an essential role in solving these problems, in a both rigorous and efficient way. Promising research directions on interference management for CR and other related multiuser communication systems are discussed.
In cognitive radio (CR) networks, there are scenarios where the secondary (lower priority) users intend to communicate with each other by opportunistically utilizing the transmit spectrum originally allocated to the existing primary (higher priority) users. For such a scenario, a secondary user usually has to trade off between two conflicting goals at the same time: one is to maximize its own transmit throughput; and the other is to minimize the amount of interference it produces at each primary receiver. In this paper, we study this fundamental tradeoff from an information-theoretic perspective by characterizing the secondary user's channel capacity under both its own transmit-power constraint as well as a set of interference-power constraints each imposed at one of the primary receivers. In particular, this paper exploits multi-antennas at the secondary transmitter to effectively balance between spatial multiplexing for the secondary transmission and interference avoidance at the primary receivers. Convex optimization techniques are used to design algorithms for the optimal secondary transmit spatial spectrum that achieves the capacity of the secondary transmission. Suboptimal solutions for ease of implementation are also presented and their performances are compared with the optimal solution. Furthermore, algorithms developed for the single-channel transmission are also extended to the case of multi-channel transmission whereby the secondary user is able to achieve opportunistic spectrum sharing via transmit adaptations not only in space, but in time and frequency domains as well.
Capacity regions are established for several two-sender, two-receiver channels with partial transmitter cooperation. First, the capacity regions are determined for compound multiple-access channels (MACs) with common information and compound MACs with conferencing. Next, two interference channel models are considered: an interference channel with common information (ICCI) and an interference channel with unidirectional cooperation (ICUC) in which the message sent by one of the encoders is known to the other encoder. The capacity regions of both of these channels are determined when there is strong interference, i.e., the interference is such that both receivers can decode all messages with no rate penalty. The resulting capacity regions coincide with the capacity region of the compound MAC with common information.
A channel with output Y = X + S + Z is examined, The state S sim N(0, QI) and the noise Z sim N(0, NI) are multivariate Gaussian random variables ( I is the identity matrix.). The input X in R^{n} satisfies the power constraint (l/n) sum_{i=1}^{n}X_{i}^{2} leq P . If S is unknown to both transmitter and receiver then the capacity is frac{1}{2} ln (1 + P/( N + Q)) nats per channel use. However, if the state S is known to the encoder, the capacity is shown to be C^{ast} =frac{1}{2} ln (1 + P/N) , independent of Q . This is also the capacity of a standard Gaussian channel with signal-to-noise power ratio P/N . Therefore, the state S does not affect the capacity of the channel, even though S is unknown to the receiver. It is shown that the optimal transmitter adapts its signal to the state S rather than attempting to cancel it.
An interference channel is a communication medium shared by M sender-receiver pairs. Transmission of information from each sender to its corresponding receiver interferes with the communications between the other senders and their receivers. This corresponds to a frequent situation in communications, and defines an M -dimensional capacity region. In this paper, we obtain general bounds on the capacity region for discrete memoryless interference channels and for linear-superposition interference channels with additive white Gaussian noise. The capacity region is determined in special cases.
A new approach to cognitive radio based on the premise that the legacy link is not fully loaded by the legacy service is presented. The assumption implies that there is a non-negligible margin to accommodate a cognitive transmission; this accommodation is achieved by spectrum shaping of the cognitive user. Much prior work on cognitive systems captures the effect of interference by the interference power level. In contrast, the current work characterizes interference by its induced degradation on the legacy user. Despite ignorance of the legacy user's message, the spectrum shaped cognitive user can always operate at its full available power. As a result, logarithmic growth of the cognitive transmission rate is achievable. In Part I of this two-part paper, analysis is provided for both scalar and vector system models where the legacy system employs coded transmission (Part II examines analog legacy users). The logarithmic growth rates, i.e., the prelog coefficients, of cognitive transmission rates in the high-power regime, are established for both the scalar and vector system models considered.
We consider three-node wireless relay channels in a Rayleigh-fading environment. Assuming transmitter channel state information (CSI), we study upper bounds and lower bounds on the outage capacity and the ergodic capacity. Our studies take into account practical constraints on the transmission/reception duplexing at the relay node and on the synchronization between the source node and the relay node. We also explore power allocation. Compared to the direct transmission and traditional multihop protocols, our results reveal that optimum relay channel signaling can significantly outperform multihop protocols, and that power allocation has a significant impact on the performance.
A relay channel consists of an input x_{l} , a relay output y_{1} , a channel output y , and a relay sender x_{2} (whose transmission is allowed to depend on the past symbols y_{1} . The dependence of the received symbols upon the inputs is given by p(y,y_{1}|x_{1},x_{2}) . The channel is assumed to be memoryless. In this paper the following capacity theorems are proved. 1)If y is a degraded form of y_{1} , then C : = : max !_{p(x_{1},x_{2})} min ,{I(X_{1},X_{2};Y), I(X_{1}; Y_{1}|X_{2})} . 2)If y_{1} is a degraded form of y , then C : = : max !_{p(x_{1})} max_{x_{2}} I(X_{1};Y|x_{2}) . 3)If p(y,y_{1}|x_{1},x_{2}) is an arbitrary relay channel with feedback from (y,y_{1}) to both x_{1} and x_{2} , then C: = : max_{p(x_{1},x_{2})} min ,{I(X_{1},X_{2};Y),I ,(X_{1};Y,Y_{1}|X_{2})} . 4)For a general relay channel, C : leq : max_{p(x_{1},x_{2})} min ,{I ,(X_{1}, X_{2};Y),I(X_{1};Y,Y_{1}|X_{2}) . Superposition block Markov encoding is used to show achievability of C , and converses are established. The capacities of the Gaussian relay channel and certain discrete relay channels are evaluated. Finally, an achievable lower bound to the capacity of the general relay channel is established.
Cognitive radios have been proposed as a means to implement efficient reuse of the licensed spectrum. The key feature of a cognitive radio is its ability to recognize the primary (licensed) user and adapt its communication strategy to minimize the interference that it generates. We consider a communication scenario in which the primary and the cognitive user wish to communicate to different receivers, subject to mutual interference. Modeling the cognitive radio as a transmitter with side-information about the primary transmission, we characterize the largest rate at which the cognitive radio can reliably communicate under the constraint that (i) no interference is created for the primary user, and (ii) the primary encoder-decoder pair is oblivious to the presence of the cognitive radio.