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The goal of the study presented in this paper is to investigate the performance of a new subcarrier allocation strategy for Orthogonal Frequency Division Multiple Access (OFDMA) multicellular networks which employ Multiple Input Multiple Output (MIMO) architecture. For this reason, a hybrid system-link level simulator has been developed executing i...
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We address the severe interference condition with unity frequency re-use factor in each cell and propose a novel distributed receiver for reliable detection of the uncoded data transmitted in multi-user multi-cell multiple input, multiple output (MIMO) systems. The new algorithm employs distributed probabilistic data association (PDA) with turbo ba...
Ziel der vorliegenden Arbeit ist die Entwicklung eines bildgebenden Radarsystems für die Füllstandmessung von Schüttgütern. Hierzu wird zunächst das räumliche Auflösungsvermögen von Radarsystemen mit mehreren Sende- und Empfangskanälen (engl. Multiple Input Multiple Output (MIMO)) analysiert und eine effiziente Signalverarbeitung vorgestellt. Ansch...
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![Simulation parameters [22].](publication/348023666/figure/tbl1/AS:995139933704192@1614271257200/Simulation-parameters-22_Q320.jpg)
The 5G technology is a promising technology to cope with the increasing demand for higher data rate and quality of service. In this paper, two proposed techniques are implemented for multiple input multiple output (MIMO) self-heterodyne OFDM system to enhance data rate and minimize the bit error rate (BER). In both of the two proposed techniques, B...
Peak-to-average power ratio (PAPR) is found to be a significant role in multiple input, multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Partial transmit sequence (PTS) is one of the effective methods to reduce the PAPR in OFDM signals. However, finding an optimum phase factor in PTS scheme is considered to be a sig...
Citations
... The SNIR for the n th UE (1 ≤ n ≤ N ) of this category, associated with the l th subcarrier (1 ≤ l ≤ N sc ) for a specific 6 VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and channel realization and assuming independent BS-UE links, is denoted as follows [27]: ...
The ever-increasing and diverse user demands as well as the need for uninterrupted access to the medium with minimum latency in dense machine type communication networks, are the key driving forces to a holistic network redesign. In this context, fifth-generation and beyond (5G/B5G) networks, incorporate various advanced physical layer techniques, such as relaying-assisted transmission, aiming to improve network performance and extend the coverage area of multicellular orientations. However, the deployment of such techniques in a cellular environment characterized by high interference levels and multi-variate channel representations, leads to increased computational complexity for radio resource management (RRM) tasks. Machine learning (ML), and especially Deep Learning (DL), is proposed as an efficient way to support end-to-end user applications in highly complex environments, since ML/DL models can relax the RRM-associated computational burden. In this paper, we consider the joint problem of relay node (RN) placement and selection subject to subcarrier allocation and power management constraints in 5G/B5G networks. Various DL-based methods are examined and combined to solve both sub-problems. The performance of these schemes is evaluated for various relaying-assisted transmission approaches, either considering known channel state information (CSI) or not. According to the derived results, total system energy efficiency (EE) and spectral efficiency (SE) can be improved by up to 30%, when considering only the DL-based RN placement scheme compared to state-of-the-art non-ML schemes. The deployment of the reinforcement learning (RL) model for RN selection, can improve EE up to 80%, while SE can be improved up to 75%, compared to a system with only DL-enabled RN placement.
... BSs are equipped with M t transmitting antennas, while users are equipped with M r receiving ones. The signal-to-noise-plus-interference-ratio (SNIR) for the n th user (1 ≤ n ≤ N ), associated with the l th subcarrier (1 ≤ l ≤ L) for a specific channel realization and assuming independently transmitted streams among different users, is defined as follows [49]: SN IR n,l = G n,n,l r n,l H r n,l I 0 + m̸ =n,l∈Sm G n,m,l ...
In this survey, a comprehensive study is provided, regarding the use of machine learning (ML) algorithms for effective resource management in fifth-generation and beyond (5G/B5G) wireless cellular networks. The ever-increasing user requirements, their diverse nature in terms of performance metrics and the use of various novel technologies, such as millimeter wave transmission, massive multiple-input-multiple-output configurations and non-orthogonal multiple access, render the multi-constraint nature of the radio resource management (RRM) problem. In this context, ML and mobile edge computing (MEC) constitute a promising framework to provide improved quality of service (QoS) for end users, since they can relax the RMM-associated computational burden. In our work, a state-of-the-art analysis of ML-based RRM algorithms, categorized in terms of learning type and potential applications as well as MEC implementations,is presented, to define the best-performing solutions for various RRM sub-problems. To demonstrate the capabilities and efficiency of ML-based algorithms in RRM, we apply and compare different ML approaches for throughput prediction, as an indicative RRM task. We investigate the problem, either as a classification or as a regression one, using the corresponding metrics in each occasion. Finally, open issues, challenges and limitations concerning AI/ML approaches in RRM for 5G and B5G networks, are discussed in detail.
... To tackle with the overall computational complexity, independent MC simulations were executed in parallel, using the developed framework in [48]. The concept of hybrid system-link level simulations is also followed in [51], where a 4G MIMO-OFDMA network has been considered. In [52], the open source framework LTE-Sim is presented. ...
In this review article, a comprehensive study is provided regarding the latest achievements in simulation techniques and platforms for fifth generation (5G) wireless cellular networks. In this context, the calculation of a set of diverse performance metrics, such as achievable throughput in uplink and downlink, the mean Bit Error Rate, the number of active users, outage probability, the handover rate, delay, latency, etc., can be a computationally demanding task due to the various parameters that should be incorporated in system and link level simulations. For example, potential solutions for 5G interfaces include, among others, millimeter Wave (mmWave) transmission, massive multiple input multiple output (MIMO) architectures and non-orthogonal multiple access (NOMA). Therefore, a more accurate and realistic representation of channel coefficients and overall interference is required compared to other cellular interfaces. In addition, the increased number of highly directional beams will unavoidably lead to increased signaling burden and handovers. Moreover, until a full transition to 5G networks takes place, coexistence with currently deployed fourth generation (4G) networks will be a challenging issue for radio network planning. Finally, the potential exploitation of 5G infrastructures in future electrical smart grids in order to support high bandwidth and zero latency applications (e.g., semi or full autonomous driving) dictates the need for the development of simulation environments able to incorporate the various and diverse aspects of 5G wireless cellular networks.
... Kelebihan dari sistem transmisi multicarrier OFDMA adalah dapat mengefisienkan penggunaan bandwidth [14]. Selain itu sistem OFDMA dapat menjaga setiap subcarrier yang satu dengan yang lain agar tetap orthogonal dan mencegah terjadinya interferensi (ISI dan ICI) pada sistem, dengan menggunakan cyclic prefix (CP). ...
Amalia Eka Rakhmania, Sholeh Hadi Pramono, Dwi Fadila Kurniawan, in this paper explain that radio over Fiber (RoF) is a technology that integrates wireless and wireline transmission system to transmit radio signal through optical fibre cable. This paper evaluates the performance of Orthogonal Frequency Division Multiple Access (OFDMA) implemented in RoF system for mobile WiMAX network. RoF channel model includes both optical fiber with Relative Intensity Noise, shot noise, thermal noise, and chromatic dispersion, and also wireless channel with Additive White Gaussian Noise (AWGN). Through simulation, signal to noise ratio (SNR), channel capacity, bit rate, and bit error rate (BER) with the influence of optical fiber length and wavelength. Result shows that optical fiber length is proportional to SNR, channel capacity, and bit rate but inversely proportional to BER. 1550 nm wavelength has better channel capacity but lesser bit rate than 1310 nm.
... Results indicate that random strategy outperforms the sequential especially for higher data rates. Finally, according to Gkonis et al. radio resource algorithm [9], each MT scavenges the available frequency subcarriers of its BS and engages those which show the best quality. In this approach CSI at the BS is considered. ...
The purpose of this paper is to examine the algorithmic quality of a semi-Random subcarrier allocation strategy and a Block Anti-Jamming Subcarrier Scavenging (BAJSS) strategy in terms of mean capacity, mean Bit Error Rate (BER), complexity as well as Jain's fairness index (power, capacity). These strategies are implemented in a LTE OFDMA multicellular network platform, which executes a fixed, sufficient for convergence, Monte Carlo (MC) runs. Both strategies are based on anti-jamming criteria so as to further mitigate Intra-Channel Interference (ICI). According to the results, semiRandom outperforms BAJSS and the traditional random strategy in terms of mean capacity, mean BER and power dissipation at the cost however of increased computational complexity.
... The Signal to Interference plus Noise Ratio (SINR) for the n th MS and s th subcarrier for a specific channel realization can be easily derived from (2) assuming independent symbol streams among MSs and subcarriers ( [7]): ...
In this paper, the performance of a proposed antenna selection algorithm is evaluated that is based on cooperative interference mitigation among neighbouring base stations. This algorithm has been evaluated in MIMO-OFDMA multicellular networks, for various bit rates per mobile user and blocking probabilities via extended Monte Carlo simulations. As results indicate, for 64QAM modulation type and 3/4/5 allocated subcarriers per mobile user, the proposed antenna selection approach can provide up to 50%/36%/25% gain on the mean number of active users in the network compared to the case where antenna selection is performed having as sole criterion the maximization of Signal to Noise Ratio.
The goal of this paper is to evaluate the performance of a proposed resource management approach that mitigates the co-channel interference (CCI) in non-orthogonal multiple access (NOMA) scenarios and maintains their enhanced spectral efficiency in distributed massive multiple input multiple output (d-massive MIMO) configurations as well. In this context, dedicated resource scheduling algorithms (RSAs) in power domain (PD) and frequency domain (FD) are studied in terms of resources’ orthogonality. Specifically, in PD case, adjusted power levels (denoted as PD-NOMA) per subcarrier and mobile terminal (MT) are assigned, while in FD case, the subcarriers are either orthogonal (FD orthogonal multiple access, FD-OMA) or non-orthogonal (FD-NOMA) to each other. The response of the d-massive MIMO system is evaluated statistically via independent Monte Carlo (MC) simulations considering a multicellular multi-user network topology and compared to typical multicellular MIMO configurations. In this framework, a simulation platform is implemented that integrates both the PD and FD RSAs. In PD, both intercell co-channel interference (Inter-CCI) and intracell co-Channel interference (Intra-CCI) are modelled analytically in order to estimate the assigned power per subcarrier and MT. In the latter case (Intra-CCI), the worst-case scenario is assumed: a subcarrier can be assigned to multiple MTs (full spectral overlapping) leading to intense Intra-CCI. In FD, two subcarrier allocation approaches are considered: Pseudo-Random or maximum signal-to-noise ratio (MSNR). The simulations in both FD implementations (FD-NOMA, FD-OMA) show that, thanks to the proposed PD-NOMA scheme, each MT requires 1/4 of the maximum available power for downlink transmission. Moreover, in any of the investigated NOMA schemes, despite the intense Intra-CCI, roughly the same number of MTs as in the OMA case can access the network. Therefore, it is straightforward that, even in worst-case scenarios, the NOMA RSAs (i) are wisely exploiting the available resources; (ii) can inherently combat intense Intra-CCI and, in this way, maintain the system’s performance (number of MTs, power savings, resilience against CCI, computation complexity). Finally, it is worth noting that in contrary to typical MIMO configurations, the d-massive MIMO architecture alone can lead up to a 13.63% increase in the system’s capacity (10% maximum allowed blocking probability, 1 tier, 1 subcarrier per MT). In this case, the increased spatial separation that is achieved, along with the exploitation of NOMA RSAs, lead to a decreased CCI (both Intra- and Inter-); hence, SNR is improved and consequently the number of accepted MTs as well.
