SER Analysis of Cell-Free Massive MIMO System

This paper presents the symbol error rate (SER) vs. signal-to-noise (SNR) ratio performance of OFDM system with QAM modulation. It has been observed that the optimal power allocation between pilot and information symbols can improve the performance gain by 2.3 dB relative to the equal power allocation between pilot and information symbols, for a system with N=3D512 sub-carriers, and a channel with L=3D40 taps. The SER performance is then compared with Rayleigh-faded as well as Rician-faded channels. It has been further concluded that the SER vs. SNR performance graph in Rayleigh-faded channel environment is better than that in Rician-faded channel. This idea implies that in OFDM case, the SER vs. SNR performance is better in scattered rich channel environments. The SER vs. SNR performance graph is degraded by equal magnitude for both equal-power and optimal-power cases, which implies that the difference between the equal-power and optimal power case is independent of the channel fading model being used. It is also observed that by varying the standard-deviation of the channel, the SER vs. SNR performance graph is not going to be affected if the channel is considered Rayleigh-faded.

Cell-free massive multiple-input multiple-output (MIMO) is considered as a promising technology for satisfying higher rate requirement of users in beyond-5G networks. This paper investigates the impact of phase noise on the performance of cell-free MIMO systems which employ a large number of multi-antenna access points (APs). For both downlink and uplink transmissions, we derive the tractable closed-form achievable rate expressions when signal detection with channel state information (CSI) and channel distribution information (CDI), respectively, by utilizing the extended deterministic equivalence method in random matrix theory. The closed-form achievable rate expressions provide efficient evaluation for the impact of phase noise on system performance. The analytical results indicate that the phase noise influences the power of the desired signal, the beamforming uncertainty gain, and the inter-user interference increment caused by the pilot contamination. In addition, the special cases that only APs have phase noise and only users have phase noise are discussed. It is found that the impact of phase noise at users is more severe than that at APs. Besides, we discuss the system performance at low and high SNR regimes. It demonstrates that the phase noise is the major limitation of the system performance in high SNR regime while it can be neglected in low SNR regime. Furthermore, we formulate the max-min power control problem for both downlink and uplink transmissions to guarantee the users' fairness and prove that the downlink max-min problem is a quasi-concave problem while the uplink max-min problem is a geometric programming (GP) problem. Then, the phase noise-aware max-min power control schemes for both downlink and uplink transmissions are proposed to ensure the users' fairness. Finally, numerical results are provided to validate the analytical results and the proposed phase noise-aware power control scheme.

Cell-free massive multiple-input multiple-output (MIMO) systems can improve transmission performance and spectral efficiency by supporting the nearby access points (APs). This paper addresses the allocation of transmission power and the optimization of user data rate for cell-free massive MIMO systems in the ultra-high reliability and low latency communication (URLLC) scenario, where all the APs simultaneously serve users over the same time/frequency resources. Considering the cell-free environment characteristics, we establish the downlink information transmission models. To guarantee the fairness among users, we aim to maximize the weighted sum rates of users by jointly user data rate optimization and transmission power allocation, subject to the constraints of the minimum data rate requirement, maximum transmission power and signal-to-interference-plus-noise ratio (SINR). Due to the complexity of the cell-free massive MIMO model, we propose a rate approximation method to find a lower bound of the weighted sum rate for the original problem. By the problem decomposition, the closed-form expression of lower bound is derived and the optimization problem is solved iteratively by using successive convex approximation and interior point methods. Simulation results confirm the effectiveness of the proposed method and show that URLLC can significantly improve transmission performance in cell-free massive MIMO networks.

Cell-free massive multiple-input multiple-output (MIMO) system is a promising architecture for next generation wireless systems by deploying a very large number of distributed access points (APs), which simultaneously serve a smaller number of user equipments (UEs) over the same time-frequency resources. It guarantees uniformly good service at high spectral efficiency with simple linear precoding techniques and max-min power control. In this article, we propose a new joint maximum-ratio and zero-forcing (JMRZF) precoding scheme, where part of APs are combined to perform centralized zero-forcing (ZF), while other APs apply simple maximum-ratio transmission (MRT). Our proposed precoder offers an adaptable trade-off between the spectral efficiency and front-haul signalling overhead. A corresponding AP subset selection scheme is also proposed which is based on large-scale fading coefficients. A closed-form expression for the achievable spectral efficiency of our proposed scheme is derived, which represents a generalized result including both fully distributed MRT and fully centralized ZF cases. Based on this closed-form expression, max-min power control is formulated and solved via the second order cone and first order methods. The former can obtain the global optimal solution, but its computational complexity is very high. On the other hand, the latter technique is sub-optimal, yet, it has very low computational complexity. Hence, it is suitable for large-scale cell-free massive MIMO systems with hundreds or thousands of APs and users. Numerical results show that our proposed JMRZF scheme can substantially outperform the local precoding schemes, even when a small part of APs are combined to deploy ZF and is implementable even when each AP has very few antennas. In addition, it is shown that our max-min power controls improves the spectral efficiency significantly, compared to the uniform power control scheme.

A cell-free massive multiple-input multiple-output (MIMO) network-assisted full-duplex (NAFD) system has been proposed to satisfy the exploding demand of higher data transmission speed and more efficient communication. However, a growing number of users in a cell-free system inevitably leads to pilot contamination. In this paper, we analyze the ergodic spectral efficiency of cell-free massive MIMO NAFD system in the presence of pilot contamination. The cell-free massive MIMO NAFD system model has been investigated and both uplink and downlink channel state information (CSI) is estimated under spatially correlated channels. Under pilot contamination, the closed-form sum-rate expressions of the uplink with maximum ratio combination (MRC) receiver while downlink with maximum ratio transmission (MRT), and uplink with zero-forcing (ZF) receiver while downlink with ZF precoding schemes are derived based on large-scale random matrix theory. Numerical results show that under several environmental settings, the theoretical results match well with the simulated results and cell-free massive MIMO NAFD system has a better performance than time-division duplex (TDD) system. Moreover, simulation results show that the achievable sum-rate of using ZF/ZF could be more spectrally efficient compared to MRC/MRT because of its interference suppression capability.

We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency.

This letter studies the performance of an uplink cell-free massive multiple-input multiple-output (MIMO) system with maximum-ratio combining receiver over Rayleigh fading channel, in which many distributed access points configured with multiple antennas provide services to multiple single-antenna users. For such a system, we derive an exact expression for probability density function (PDF) of individual signal-to-interference-plus-noise ratio (SINR). Due to its complexity for performance evaluation purposes, this PDF of SINR is approximated as a gamma distribution, and the resulting expression is used to obtain the approximate expressions of the coverage probability and the ergodic capacity, respectively. Besides, in order to ensure uniformly good coverage probability and ergodic capacity, a max-min power control algorithm is proposed, which can be formed by solving a geometric programming problem. Numerical results verify the correctness of the theoretical analysis and confirm the effectiveness of the proposed algorithm.

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free Massive MIMO systems with the assistance of an RIS for enhancing the system performance under the presence of spatial correlation among the engineered scattering elements of the RIS. Distributed maximum-ratio processing is considered at the access points (APs). We introduce an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">aggregated channel</i> estimation approach that provides sufficient information for data processing with the main benefit of reducing the overhead required for channel estimation. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expressions for the uplink and downlink ergodic net throughput are formulated in terms of only the channel statistics. Based on the obtained analytical frameworks, we unveil the impact of channel correlation, the number of RIS elements, and the pilot contamination on the net throughput of each user. In addition, a simple control scheme for optimizing the configuration of the engineered scattering elements of the RIS is proposed, which is shown to increase the channel estimation quality, and, hence, the system performance. Numerical results demonstrate the effectiveness of the proposed system design and performance analysis. In particular, the performance benefits of using RISs in Cell-Free Massive MIMO systems are confirmed, especially if the direct links between the APs and the users are of insufficient quality with high probability.

Cell-free massive multiple-input multiple-output (MIMO) is considered as a promising technology for providing uniformly good services in future networks. The aim of this paper is to provide the first comparison of the uplink performance of cell-free massive MIMO systems with low-resolution analogto-digital converters under the zero-forcing (ZF) and maximum ratio combining (MRC) receivers. By utilizing an addictive quantization model, a novel closed-form uplink spectral efficiency (SE) expression is derived for the ZF receiver. Moreover, the energy efficiency (EE) of the considered system is analyzed. In contrast to previous works, it turns out that the ZF receiver outperforms the MRC receiver with a large number of quantization bits in terms of SE and EE. Furthermore, it is interesting to find that a better EE-SE trade-off can be achieved by employing a large number of antennas at the access point. Finally, pilot assignment schemes are used to minimize the pilot contamination and a maxmin power control scheme is proposed to improve both SE and EE performance.

In an era where ubiquitous connectivity and escalating data demands are altering the landscape of wireless communications, our paper proposes a pioneering enhancement for the OMNeT++ simulator to support the advanced features of IEEE 802.11ax high efficiency (HE) alongside cell-free massive multiple-input multiple-output (MIMO) systems. Traditional wireless networks face daunting challenges in sustaining elevated quality of service (QoS), primarily due to fluctuating user densities and signal quality. Cell-free massive MIMO serves as a compelling answer to this predicament by decentralizing the cellular architecture. It eradicates conventional cell boundaries, furnishing uniform QoS regardless of user locations. However, these advancements come at the expense of complex backhaul networks and articulated joint signal processing. The 802.11ax standard, touted for its robustness and efficiency, remains underexplored in this new paradigm. Our research not only dissects the architectural elements and constraints of both 802.11ax and cell-free massive MIMO but also elaborates on the adaptations required to extend OMNeT++ functionalities for these technologies. By doing so, we bridge a crucial gap, enabling the simulator to provide a more precise, detailed, and scalable evaluation of emerging 6G scenarios and directional communications also taking into account the impact of the most known routing protocols such as dynamic source routing (DSR), ad hoc on-demand distance vector routing (AODV), optimized link state routing (OLSR), and dynamic mobile ad hoc network on-demand (DYMO) that were selected for this comparative study. The proposed extensions promise to revolutionize network simulations and lay the foundation for in-depth analyses of wireless systems in complex and dynamic environments. Through extensive simulations, our study demonstrates that cell-free massive MIMO configurations significantly improve network throughput in high-density mobile ad hoc network (MANET) environments, with results indicating an average throughput gain of up to 30% compared with non-cell-free configurations. This improvement highlights the efficacy of cell-free massive MIMO to take advantage of the spatial and frequency multiplexing capabilities inherent in the 802.11ax standard, making it a promising solution for future wireless systems in densely populated areas.

In this paper, performance metric of orthogonal frequency division multiplexing (OFDM) system is analyzed over a composite fading channel, i.e., generalized K-fading channel. Here, OFDM system is considered which includes repetition code to enhance the wireless link performance with simplicity. Symbol error rate (SER) performance is evaluated using binary phase shift keying (BPSK) and 16-quadrature amplitude modulation (16-QAM) over generalized K-fading channel. This channel model considers Nakagami-m distribution to define multipath and gamma distribution to represent shadowing effects. Simulation results demonstrate that improved system performance can be achieved by using repetition code in severely faded environment. A comparative study of coded and uncoded system is also given in this paper. Consequently, SER performance is improved with the increase of shape parameters.

SER performance investigation of a MPPM relay-aided FSO system with three decision thresholds over EW fading channel considering pointing errors

Traditional beamforming and power control algo-rithms in cognitive radio (CR) are based on the assumption of perfect channel state information (CSI) however; this may lead to performance degradation in realistic systems.In this paper, the problem of joint beamforming and power control is investigated in underlay CR networks with imperfect CSI.Our objective is to maximize the sum utility of secondary users (SUs) under the primary users (PUs) interference power constraints and the transmission power constraint of SUs.First, the joint beamforming and power control problem is formulated under game theory framework, where the SUs compete with each other over the beamforming vectors and transmission power level made available by the PUs.Moreover, the channel uncertainty is described using ellipsoid sets and the interference power constraints can be converted into robust interference power constraints.Besides, Nash equilibrium (NE) is considered as the solution of this game.Finally, simulation results show that the proposed scheme can converge to a locally optimal pair of beamforming vector and transmission power level in the presence of channel uncertainty.

It is predicted that there will be billions of machine type communication (MTC) devices to be deployed in near future. This will certainly cause severe access congestion and system overload which is one of the major challenges for the proper operation of 5G networks. Adopting device-to-device (D2D) communications into massive multiple-input multiple-output (MIMO) systems has been considered as a potential solution to alleviate the overload of MTC devices by offloading the MTC traffic onto D2D links. This work proposes a novel pilot reuse (PR) and power control (PC) for energy efficiency (EE) optimization of the uplink D2D underlaying massive MIMO cellular systems. Although the use of large scale antenna array at the base station (BS) can eliminate most of the D2D-to-Cellular interference, the Cellular-to-D2D interference and the channel estimation error caused by PR will remain significant. Motivated by this, and in order to reduce the channel estimation error, in this paper a novel heuristic PR optimum pilot reuse scheme is proposed for D2D transmitters (D2DTs) selection. By taking into account the interference among users as well as the overall power consumption, the overall system EE is maximized through power optimization while maintaining the quality-of-service (QoS) provisions for both cellular users (CUEs) and D2D pairs. The power optimization problem is modeled as a non-cooperative game and, as such, a distributed iterative power control algorithm which optimizes users power sequentially is proposed. Various performance evaluation results obtained by means of computer simulations have shown that the proposed PR scheme and PC algorithm can significantly increase the overall system EE.

Cell-free massive multiple-input multiple-output (MIMO) is a novel beyond 5G (B5G) and 6G paradigm that, through the use of a common central processing unit (CPU), coordinates a large number of distributed access points (APs) to coherently serve mobile stations (MSs) on the same time/frequency resource. By exploiting the characteristics of new less-congested millimeter wave (mmWave) frequency bands, these networks can improve the overall system spectral and energy efficiencies by using low-complexity hybrid precoders/decoders. For this purpose, the system must be correctly dimensioned to provide the required quality of service (QoS) to MSs under different traffic load conditions. However, only heavy traffic load conditions are usually taken into account when analysing these networks and, thus, many APs might be underutilized during low traffic load periods, leading to an inefficient use of resources and waste of energy. Aiming at the implementation of energy-efficient AP switch on/off strategies, several approaches have been proposed in the literature that only consider rather unrealistic uniform spatial traffic distribution in the whole coverage area. Unlike prior works, this paper proposes energy efficient AP sleep-mode techniques for cell-free mmWave massive MIMO networks that are able to capture the inhomogeneous nature of spatial traffic distribution in realistic wireless networks. The proposed framework considers, analyzes and compares different AP switch ON-OFF (ASO) strategies that, based on the use of goodness-of-fit (GoF) tests, are specifically designed to dynamically turn on/off APs to adapt to both the number and the statistical distribution of MSs in the network. Numerical results show that the use of properly designed GoF-based ASO strategies under a non-uniform spatial traffic distribution can serve to considerably improve the achievable energy efficiency.