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Towards Optimal Energy Efficiency in Cell-Free Massive MIMO Systems ; ; et al in IEEE Transactions on Green Communications and Networking (2021), 5(2), 816-831 Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink ... [more ▼] Motivated by the ever-growing demand for green wireless communications and the advantages of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems, we focus on the design of their downlink (DL) for optimal energy efficiency (EE). To address this fundamental topic, we assume that each access point (AP) is deployed with multiple antennas and serves multiple users on the same time-frequency resource while the APs are Poisson point process (PPP) distributed, which approaches realistically their opportunistic spatial randomness. Relied on tools from stochastic geometry, we derive a lower bound on the DL average achievable spectral efficiency (SE). Next, we consider a realistic power consumption model for CF mMIMO systems. These steps enable the formulation of a tractable optimization problem concerning the DL EE, which results in the analytical determination of the optimal pilot reuse factor, the AP density, and the number of AP antennas and users that maximize the EE. Hence, we provide useful design guidelines for CF mMIMO systems relating to fundamental system variables towards optimal EE. Among the results, we observe that an optimal pilot reuse factor and AP density exist, while larger values result in an increase of the interference, and subsequently, lower EE. Overall, it is shown that the CF mMIMO technology is a promising candidate for next-generation networks achieving simultaneously high SE and EE. [less ▲] Detailed reference viewed: 26 (4 UL)Coverage Probability of Distributed IRS Systems Under Spatially Correlated Channels ; ; et al in IEEE Wireless Communications Letters (2021) This paper suggests the use of multiple distributed intelligent reflecting surfaces (IRSs) towards a smarter control of the propagation environment. Notably, we also take into account the inevitable ... [more ▼] This paper suggests the use of multiple distributed intelligent reflecting surfaces (IRSs) towards a smarter control of the propagation environment. Notably, we also take into account the inevitable correlated Rayleigh fading in IRS-assisted systems. In particular, in a single-input and single-output (SISO) system, we consider and compare two insightful scenarios, namely, a finite number of large IRSs and a large number of finite size IRSs to show which implementation method is more advantageous. In this direction, we derive the coverage probability in closed-form for both cases contingent on statistical channel state information (CSI) by using the deterministic equivalent (DE) analysis. Next, we obtain the optimal coverage probability. Among others, numerical results reveal that the addition of more surfaces outperforms the design scheme of adding more elements per surface. Moreover, in the case of uncorrelated Rayleigh fading, statistical CSI-based IRS systems do not allow the optimization of the coverage probability. [less ▲] Detailed reference viewed: 20 (0 UL)Coverage Probability of Double-IRS Assisted Communication Systems ; ; Chatzinotas, Symeon et al in IEEE Wireless Communications Letters (2021), 10(8), 1722-1726 In this paper, we derive the coverage probability of a double-intelligent reflecting surface (IRS) assisted wireless network and study the impact of multiplicative beamforming gain and correlated Rayleigh ... [more ▼] In this paper, we derive the coverage probability of a double-intelligent reflecting surface (IRS) assisted wireless network and study the impact of multiplicative beamforming gain and correlated Rayleigh fading. In particular, we derive a novel closed-form expression of the coverage probability of a single-input single-output (SISO) system assisted by two large IRSs while being dependent on the corresponding arbitrary reflecting beamforming matrices (RBMs) and large-scale statistics in terms of correlation matrices. Taking advantage of th large-scale statistics, we achieve to perform optimization of the RBM of both IRSs at every several coherence intervals rather at each interval. This property, based on statistical channel state information (CSI), is of paramount importance in multi-IRS assisted networks, which are accompanied with increased computational complexity during their RBM optimization. Numerical results validate the tightness of the analytical results even for small IRSs and reveal insightful properties. [less ▲] Detailed reference viewed: 21 (1 UL)Federated Learning for Physical Layer Design ; ; Chatzinotas, Symeon in IEEE Communications Magazine (2021) Model-free techniques, such as machine learning (ML), have recently attracted much interest towards the physical layer design, e.g., symbol detection, channel estimation, and beamforming. Most of these ML ... [more ▼] Model-free techniques, such as machine learning (ML), have recently attracted much interest towards the physical layer design, e.g., symbol detection, channel estimation, and beamforming. Most of these ML techniques employ centralized learning (CL) schemes and assume the availability of datasets at a parameter server (PS), demanding the transmission of data from edge devices, such as mobile phones, to the PS. Exploiting the data generated at the edge, federated learning (FL) has been proposed recently as a distributed learning scheme, in which each device computes the model parameters and sends them to the PS for model aggregation while the datasets are kept intact at the edge. Thus, FL is more communication-efficient and privacy-preserving than CL and applicable to the wireless communication scenarios, wherein the data are generated at the edge devices. This article presents the recent advances in FL-based training for physical layer design problems. Compared to CL, the effectiveness of FL is presented in terms of communication overhead with a slight performance loss in the learning accuracy. The design challenges, such as model, data, and hardware complexity, are also discussed in detail along with possible solutions. [less ▲] Detailed reference viewed: 25 (1 UL)Scalable Cell-Free Massive MIMO Systems: Impact of Hardware Impairments ; ; et al in IEEE Transactions on Vehicular Technology (2021), 70(10), 9701-9715 Scalable cell-free CF (SCF) massive multiple-input-multiple-output (mMIMO) systems is a promising technology to cover the demands for higher data rates and increasing number of users in fifth generation ... [more ▼] Scalable cell-free CF (SCF) massive multiple-input-multiple-output (mMIMO) systems is a promising technology to cover the demands for higher data rates and increasing number of users in fifth generation (5G) networks and beyond. According to this concept, a large number of distributed access points (APs) communicates with the users in the network by means of joint coherent transmission while facing the main challenges against standard CF mMIMO systems being their high fronthaul load and computational complexity. Given that the cost-efficient deployment of such large networks requires low-cost transceivers being prone to unavoidable hardware imperfections, in this work, we focus on their impact on the advantageous SCF mMIMO systems by means of a general model accounting for both additive and multiplicative hardware impairments (HWIs). Notably, the scalability, depending on the time-variant characteristics of the network, is clearly affected by means of HWIs being time-varying. There is no other work in the literature studying the phase noise (PN) in CF mMIMO systems or in general any HWIs in SCF mMIMO systems. Hence, we derive upper and lower bounds on the uplink capacity accounting for HWIs. Especially, the lower bound is derived in closed-form by means of the theory of deterministic equivalents (DEs) and after obtaining the optimal hardware-aware (HA) partial minimum mean-squared error (PMMSE) combiner. Among the interesting findings, we observe that separate local oscillators (SLOs) outperform a common LO (CLO) architecture, and the additive transmit distortion degrades more the performance than the receive distortion. [less ▲] Detailed reference viewed: 32 (1 UL)Intelligent Reflecting Surface-assisted MU-MISO Systems with Imperfect Hardware: Channel Estimation and Beamforming Design ; ; et al Poster (2021) Intelligent reflecting surface (IRS), consisting of lowcost passive elements, is a promising technology for improving the spectral and energy efficiency of the fifth-generation (5G) and beyond networks ... [more ▼] Intelligent reflecting surface (IRS), consisting of lowcost passive elements, is a promising technology for improving the spectral and energy efficiency of the fifth-generation (5G) and beyond networks. It is also noteworthy that an IRS can shape the reflected signal propagation. Most works in IRSassisted systems have ignored the impact of the inevitable residual hardware impairments (HWIs) at both the transceiver hardware and the IRS while any relevant works have addressed only simple scenarios, e.g., with single-antenna network nodes and/or without taking the randomness of phase noise at the IRS into account. In this work, we aim at filling up this gap by considering a general IRS-assisted multi-user (MU) multiple-input single-output (MISO) system with imperfect channel state information (CSI) and correlated Rayleigh fading. In parallel, we present a general computationally efficient methodology for IRS reflect beamforming (RB) optimization. Specifically, we introduce an advantageous channel estimation (CE) method for such systems accounting for the HWIs. Moreover, we derive the uplink achievable spectral efficiency (SE) with maximal-ratio combining (MRC) receiver, displaying three significant advantages being: 1) its closed-form expression, 2) its dependence only on large-scale statistics, and 3) its low training overhead. Notably, by exploiting the first two benefits, we achieve to perform optimization with respect to the that can take place only at every several coherence intervals, and thus, reduces significantly the computational cost compared to other methods which require frequent phase optimization. Among the insightful observations, we highlight that uncorrelated Rayleigh fading does not allow optimization of the SE, which makes the application of an IRS ineffective. Also, in the case that the phase drifts, describing the distortion of the phases in the RBM, are uniformly distributed, the presence of an IRS provides no advantage. The analytical results outperform previous works and are verified by Monte-Carlo (MC) simulations. [less ▲] Detailed reference viewed: 34 (5 UL)Deep Channel Learning For Large Intelligent Surfaces Aided mm-Wave Massive MIMO Systems ; ; et al in IEEE Wireless Communications Letters (2020), 9(Sept. 2020), 1447-1451 This letter presents the first work introducing a deep learning (DL) framework for channel estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multiple-output) systems. A ... [more ▼] This letter presents the first work introducing a deep learning (DL) framework for channel estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multiple-output) systems. A twin convolutional neural network (CNN) architecture is designed and it is fed with the received pilot signals to estimate both direct and cascaded channels. In a multi-user scenario, each user has access to the CNN to estimate its own channel. The performance of the proposed DL approach is evaluated and compared with state-of-the-art DL-based techniques and its superior performance is demonstrated. [less ▲] Detailed reference viewed: 51 (4 UL)Performance Analysis of Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach ; ; et al in IEEE Transactions on Vehicular Technology (2020) Cell-free (CF) massive multiple-input-multiple-output (MIMO) has emerged as an alternative deployment for conventional cellular massive MIMO networks. As revealed by its name, this topology considers no ... [more ▼] Cell-free (CF) massive multiple-input-multiple-output (MIMO) has emerged as an alternative deployment for conventional cellular massive MIMO networks. As revealed by its name, this topology considers no cells, while a large number of multi-antenna access points (APs) serves simultaneously a smaller number of users over the same time/frequency resources through time-division duplex (TDD) operation. Prior works relied on the strong assumption (quite idealized) that the APs are uniformly distributed, and actually, this randomness was considered during the simulation and not in the analysis. However, in practice, ongoing and future networks become denser and increasingly irregular. Having this in mind, we consider that the AP locations are modeled by means of a Poisson point process (PPP) which is a more realistic model for the spatial randomness than a grid or uniform deployment. In particular, by virtue of stochastic geometry tools, we derive both the downlink coverage probability and achievable rate. Notably, this is the only work providing the coverage probability and shedding light on this aspect of CF massive MIMO systems. Focusing on the extraction of interesting insights, we consider small-cells (SCs) as a benchmark for comparison. Among the findings, CF massive MIMO systems achieve both higher coverage and rate with comparison to SCs due to the properties of favorable propagation, channel hardening, and interference suppression. Especially, we showed for both architectures that increasing the AP density results in a higher coverage which saturates after a certain value and increasing the number of users decreases the achievable rate but CF massive MIMO systems take advantage of the aforementioned properties, and thus, outperform SCs. In general, the performance gap between CF massive MIMO systems and SCs is enhanced by increasing the AP density. Another interesting observation concerns that a higher path-loss exponent decreases the rate while the users closer to the APs affect more the performance in terms of the rate. [less ▲] Detailed reference viewed: 93 (5 UL)Impact of residual transceiver impairments on MMSE filtering performance of Rayleigh-product MIMO channels Sharma, Shree Krishna ; ; Chatzinotas, Symeon et al in Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2017) (2017, July) ecent studies have demonstrated the presence of residual transceiver hardware impairments even after employing calibration and compensation techniques in different wireless systems. The effect of these ... [more ▼] ecent studies have demonstrated the presence of residual transceiver hardware impairments even after employing calibration and compensation techniques in different wireless systems. The effect of these impairments becomes more severe in the systems involving a large number of inexpensive Radio Frequency (RF) chains such as massive Multiple Input Multiple Output (MIMO) systems due to the requirement of cost-efficient implementation. However, most of the existing studies consider ideal transceivers without incorporating the effect of residual hardware impairments. In this regard, this paper studies the impact of additive residual transceiver hardware impairments on the Minimum Mean Square Error (MMSE) filtering performance of Rayleigh-Product (RP) MIMO channels. Using principles from Random Matrix Theory (RMT), the MMSE filtering performance of the RP channels is analyzed and a tight lower bound is derived by taking the effects of residual additive transceiver impairments into account. Moreover, some useful insights on the performance of the considered system with respect to various parameters such as the transmit Signal to Noise Ratio (SNR), the number of scatterers and the severity of impairments on both the transmit and receive sides are provided. [less ▲] Detailed reference viewed: 79 (0 UL)Impact of Residual Additive Transceiver Hardware Impairments on Rayleigh-Product MIMO Channels with Linear Receivers: Exact and Asymptotic Analyses ; Sharma, Shree Krishna ; et al in IEEE Transactions on Communications (2017) Detailed reference viewed: 164 (15 UL)Impact of Transceiver Hardware Impairments on the Ergodic Channel Capacity for Rayleigh-Product MIMO Channels ; Sharma, Shree Krishna ; Chatzinotas, Symeon et al in Proceedings of IEEE SPAWC 2016 (2016, July) This paper aims at a realistic evaluation of Rayleighproduct multiple-input multiple-output (MIMO) systems. Specifically, by considering the residual transceiver hardware impairments into account, we ... [more ▼] This paper aims at a realistic evaluation of Rayleighproduct multiple-input multiple-output (MIMO) systems. Specifically, by considering the residual transceiver hardware impairments into account, we derive the ergodic channel capacity of a MIMO system with optimal receivers in the case of insufficient scattering. Actually, motivated by the increasing interest for massive MIMO systems, we investigate the impact of transceiver hardware imperfections in systems with both finite (conventional) and large number of antennas under rank deficient channel matrix conditions by varying the severity of hardware quality. Among the interesting outcomes, we emphasize that the residual hardware transceiver impairments result to a saturation of the ergodic channel capacity within the high signal-to-noise ratio (SNR) regime. Furthermore, we observe that the higher the “richness” of the scattering environment, the higher the ergodic channel capacity till it gets saturated. [less ▲] Detailed reference viewed: 196 (19 UL)MMSE Filtering Performance of DH-AF Massive MIMO Relay Systems with Residual Transceiver Impairments ; Sharma, Shree Krishna ; Chatzinotas, Symeon in Proceedings of IEEE ICC 2016 (2016, May) The emerging requirements of the fifth generation (5G) wireless communications are high spectral efficiency, low latency, and ubiquitous coverage. In this direction, Dual-Hop (DH) Amplify-and-Forward (AF ... [more ▼] The emerging requirements of the fifth generation (5G) wireless communications are high spectral efficiency, low latency, and ubiquitous coverage. In this direction, Dual-Hop (DH) Amplify-and-Forward (AF) relaying has been widely investigated due to its simplicity, low implementation complexity and low transmission delay. However, most existing works assume ideal transceiver hardware which is impractical. In practice, a cost-efficient wireless transceiver has to combat the effects of several inevitable impairments such as high power amplifier nonlinearities, In-phase/Quadrature-phase (I/Q)-imbalance, and oscillator phase noise, which can be only partially compensated using calibration algorithms. In this direction, this paper analyzes the Minimum Mean Square Error (MMSE) filtering performance of a DH-AF Multiple-Input-Multiple-Output (MIMO) wireless system considering the effects of the residual additive impairments at the transmitter and receiver of both hops. Using free probability principles, the MMSE filtering performance of the considered system is studied and a tight lower bound is proposed by taking the effects of residual additive transceiver impairments into account. Our numerical results show that the MMSE filtering performance of the DH-AF massive MIMO relay system significantly degrades and results to saturation in the presence of residual additive transceiver impairments. [less ▲] Detailed reference viewed: 202 (4 UL)Impact of Transceiver Impairments on the Capacity of Dual-Hop Relay Massive MIMO Systems ; Sharma, Shree Krishna ; Chatzinotas, Symeon in Proceedings of IEEE Globecom 2015 (2015, December) Despite the deleterious effect of hardware impairments on communication systems, most prior works have not investigated their impact on widely used relay systems. Most importantly, the application of ... [more ▼] Despite the deleterious effect of hardware impairments on communication systems, most prior works have not investigated their impact on widely used relay systems. Most importantly, the application of inexpensive transceivers, being prone to hardware impairments, is the most cost-efficient way for the implementation of massive multiple-input multiple-output (MIMO) systems. Consequently, the direction of this paper is towards the investigation of the impact of hardware impairments on MIMO relay networks with large number of antennas. Specifically, we obtain the general expression for the ergodic capacity of dual-hop (DH) amplify-and-forward (AF) relay systems. Next, given the advantages of the free probability (FP) theory with comparison to other known techniques in the area of large random matrix theory, we pursue a large limit analysis in terms of number of antennas and users by shedding light to the behavior of relay systems inflicted by hardware impairments. [less ▲] Detailed reference viewed: 120 (4 UL) |
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