Weighted sum rate optimization for downlink multiuser MIMO systems with per antenna power constraint: Downlink-uplink duality approach

<p>This thesis considers the analysis of current and future cellular communication systems. The main focus is on multiuser multiple-input multiple-output (MU-MIMO) antenna systems. The goal of this work is to characterize the achievable spectral efficiency of MU-MIMO systems, as well as to analyze the performance of practical, linear MU-MIMO transceiver structures in heterogeneous propagation environments. The analytical derivations in this thesis are based on the mathematical theory of finite and large dimensional random matrices. A collection of new general random matrix theory results, which permit efficient numerical evaluation are derived. With downlink regularized zero-forcing (RZF) processing at a cellular base station (BS), a general framework for the analysis of the expected (average) signal-to-interference-plus-noise-ratio (SINR) and ergodic sum spectral efficiency is developed for uncorrelated and semi-correlated Rayleigh fading, as well as uncorrelated Ricean fading propagation channels. In contrast to existing results, the presented analyses are extremely general, applicable to single-cellular, multi-cellular, as well as distributed antenna systems. These systems could consist of arbitrary numbers of transmit and receive antennas, link signal-to-noise-ratios (SNRs), equal and unequal transmit correlation structures, and line-of-sight (LoS) levels, respectively. Numerical results are presented for single-cellular, as well as for two-tier multi-cellular systems demonstrating the impact of novel BS coordination strategies to suppress dominant inter-cellular interference. With dominant LoS directions in the propagation channel, the instantaneous downlink zero-forcing (ZF) SNR of a given terminal is analyzed. The ZF SNR is shown to be approximated by a gamma distribution for any number of transmit and receive antennas, link SNRs, and LoS levels. Furthermore, for moderately sized MU-MIMO systems, simplified instantaneous and ergodic sum spectral efficiency analyses are presented with RZF, ZF and matched-filter (MF) transmission on the downlink, and minimum-mean-squared-error, ZF and maximum-ratio combining (MRC) on the uplink, respectively. The simple nature of the derived expressions lead to the discovery of several valuable system level insights as a function of the contributing network parameters. Numerical results are presented for conventional and moderate MU-MIMO systems. Considering downlink semi-correlated Rayleigh fading channels with spatial correlation at the BS, it is mathematically proven that common correlation patterns for each terminal predicts lower ergodic sum spectral efficiencies in comparison to terminal specific correlation patterns. Closed-form approximations for the expected SINR and ergodic sum spectral efficiency are derived for both MF and ZF precoding, demonstrating the sensitivity of unequal correlation structures on the expected signal, interference and noise powers, respectively. The presented numerical results provide a cautionary tale of the impact of unequal correlation patterns on MU-MIMO performance and the importance of modeling this phenomenon. Finally, an approximate uplink performance analysis of large MU-MIMO systems with MRC and space-constrained uniform linear antenna arrays (ULA) is presented for semi-correlated Ricean fading channels. A space-constrained channel model is proposed, encapsulating the effects of unequal receive spatial correlation, unequal LoS levels, and unequal link gains for each terminal. The per-terminal and cell-wide ergodic sum spectral efficiencies are characterized and numerous practical special cases are presented. A limiting analysis of the ergodic per-terminal and cell-wide spectral efficiencies is also carried out, as the number of BS antennas grow without bound with a finite number of terminals and fixed physical dimensions of the ULA. Numerical results demonstrate the impact of space-constrained ULAs on the MU-MIMO system performance with variation in the LoS levels, correlation structures, physical array dimensions, and system size, respectively.</p>

In this paper, we discuss the influence of feedback channel delay on throughput of linear multi-user multiple-input multiple-output (MIMO) systems employing vector quantization (VQ) algorithms for encoding channel state information (CSI). We consider an approach where the mobile receiver estimates the downlink channel and chooses one of the predefined channel characterization codewords whose indices are transmitted back to the base station transmitter. In practice, the feedback channel introduces delay in transmission of the indices and we evaluate the resulting channel throughput loss for different system setups. Moreover, we define two new parameters of VQ MIMO systems: the channel eigenmode coherence time and singular value coherence time, and discuss their influence on system design. We demonstrate the performance of two types of systems, one using time division multiplexing of individual mobile users and another transmitting to multiple users at the same time. The simulation results show that feedback delay sensitivity of the multiple-user system throughput is much higher than in the TDM approach. Based on those results we propose a simple method allowing a selection of the VQ resolution for the given channel characteristics and system setup.

Expressions are derived for the coverage probability and average rate of both multi-user multiple input multiple output (MU-MIMO) and single input multiple output (SIMO) systems in the context of a fractional frequency reuse (FFR) scheme. In particular, given a reuse region of $\frac{1}{3}$ (FR3) and a reuse region of 1 (FR1) as well as a signal-to-interference-plus-noise-ratio (SINR) threshold $S_{th}$ , which decides the user assignment to either the FR1 or FR3 regions, we theoretically show that: $1)$ the optimal choice of $S_{th}$ which maximizes the coverage probability is $S_{th} = T$ , where $T$ is the target SINR required for ensuring adequate coverage, and $2)$ the optimal choice of $S_{th}$ which maximizes the average rate is given by $S_{th}= T^{\prime}$ , where $T^{\prime}$ is a function of the path loss exponent, the number of antennas and of the fading parameters. The impact of frequency domain correlation amongst the OFDM sub-bands allocated to the FR1 and FR3 cell-regions is analysed and it is shown that the presence of correlation reduces both the coverage probability and the average throughput of the FFR network. Furthermore, the performance of our FFR-aided MU-MIMO and SIMO systems is compared. Our analysis shows that the (2 $\times$ 2) MU-MIMO system achieves 22.5% higher rate than the (1 $\times$ 3) SIMO system and for lower target SINRs, the coverage probability of a (2 $\times$ 2) MU-MIMO system is comparable to a (1 $\times$ 3) SIMO system. Hence the former one may be preferred over the latter. Our simulation results closely match the analytical results.

The past ten years have seen notable research activity and significant advancements in multiuser multiple-input multiple-output (MU-MIMO) antennas. An MU-MIMO antenna system must accommodate many subscribers without additional bandwidth or energy. User scheduling becomes a critical strategy to take advantage of multiuser heterogeneity and acquire maximum gain in systems where the total number of recipients exceeds the number of transmitting antennas. Due to their high computational cost, many user selection methods currently in use, such as greedy algorithms and exhaustive search are unsuitable for MU-MIMO systems. A suitable scheduling mechanism is essential for the various users in an MU-MIMO system to utilise bandwidth and enhance the system’s total rate effectively. In this article, we proposed a user and antenna scheduling with a population-based meta-heuristic approach, namely the binary salp swarm algorithm (binary SSA), to increase the system sum rate with low computing complexity. We specifically used a population-based meta-heuristics optimisation technique to simulate the user scheduling problem in MU-MIMO systems, characterising complicated issues with binary decisions. Additionally, binary SSA significantly outperforms existing population-based models, such as the binary bat algorithm (binary BA), PSO, SSA, FPA and binary flower pollination algorithm (binary FPA), regarding system throughput/sum rate. The proposed binary SSA technique also effectively achieves a system sum rate compared to a random search scheme and other existing suboptimal scheduling methods. Compared to binary BA and binary FPA approaches, the binary SSA has a higher convergence rate and superior searching capabilities. The simulation outcomes show the proposed binary SSA-based scheduling scheme delivers noticeable performance benefits.

This paper propose an iterative inter-cell interference coordination strategy to meet the requirements of the next generation mobile communication systems, which are higher data rate, broader coverage, especially more stringent demand on cell edge spectral efficiency. Sector cooperation is introduced in MU MIMO (multi-user multiple input multiple output) systems. In the aspect of user pairing, both the system capacity and fairness among users are taken into consideration through pairing center and edge users. As for the inter-cell interference coordination, iterative sector cooperation on selecting pre-coders from code books is implemented, in order to avoid inter-cell interference and improve cell edge performance. Theoretical analysis and simulation results demonstrate that the proposed strategy can significantly improve cell edge throughput while guaranteeing the performance of average cell spectrum efficiency.

This paper considers a multi-user multiple-input multiple-output (MU-MIMO) system where the downlink communication between a base station (BS) and multiple user equipments (UEs) is aided by a reconfigurable intelligent surface (RIS). We study the sum rate maximization problem with the objective of finding the optimal precoding vectors and RIS configuration. Due to fronthaul limitation, each entry of the precoding vectors must be picked from a finite set of quantization labels. Furthermore, two scenarios for the RIS are investigated, one with continuous infinite-resolution reflection coefficients and another with discrete finite-resolution reflection coefficients. A novel framework is developed which, in contrast to the common literature that only offers sub-optimal solutions for optimization of discrete variables, is able to find the optimal solution to problems involving discrete constraints. Based on the classical weighted minimum mean square error (WMMSE), we transform the original problem into an equivalent weighted sum mean square error (MSE) minimization problem and solve it iteratively. We compute the optimal precoding vectors via an efficient algorithm inspired by sphere decoding (SD). For optimizing the discrete RIS configuration, two solutions based on the SD algorithm are developed: An optimal SD-based algorithm and a low-complexity heuristic method that can efficiently obtain RIS configuration without much loss in optimality. The effectiveness of the presented algorithms is corroborated via numerical simulations where it is shown that the proposed designs are remarkably superior to the commonly used benchmarks.

Multiple input multiple output (MIMO) systems have high potential to achieve maximum channel capacity in wireless communication systems. Multi-user (MU) MIMO network with transmit antennas $$T_x$$ at base station can schedule as many single antenna users in one time slot. This necessitates incorporation of a user scheduling strategy. Maximizing sumrate performance without under utilization of channel resources is a primary objective of such scheduling algorithms. Another key design factor for such techniques is to optimize fairness i.e. allowing equal opportunity to all communicating entities. In this paper, we present a simple approach to solve the scheduling problem in MU-MIMO systems while addressing the conflicting objectives of sumrate and fairness. Two variants of the proposed method are also discussed that provide options for maximizing the cumulative sumrate and improving the fairness. Simulations validate the proposed algorithm as a better choice over other conventional methods as it achieves optimal performance with relatively less computational complexity and without compromising fairness. Fairness results are verified by average sumrate method and Jain’s Fariness Index.

This work presents a first comprehensive analysis of the impact of vector coded caching (VCC) in multi-user multiple-input multiple-output (MU-MIMO) systems with multiple receive antennas and variable pathloss — two key factors that critically influence systems with inherent MU unicasting behavior. We investigate two widely adopted precoding strategies: (i) block-diagonalization (BD) at the transmitter combined with maximal ratio combining (MRC) at the receivers, and (ii) zero-forcing (ZF) precoding. Our analysis explicitly accounts for practical considerations such as channel fading, channel state information (CSI) acquisition overhead, and fairness-oriented power allocation. Our contributions span both analytical and simulation-based fronts. On the analytical side, we derive analytical expressions for the achievable throughput under BD-MRC and ZF, highlighting the performance benefits of equipping multi-antenna users with cache-aided interference management. Specifically, we develop a low-complexity BD-MRC optimization method that leverages matrix structure to significantly reduce the dimensionality involved in precoding computation, followed by solving the associated max-min fairness problem through an efficient one-dimensional search. In the massive MIMO regime, an asymptotic expression for the achievable throughput over Rayleigh fading channels is also derived. Simulations validate our theoretical results, confirming that VCC delivers substantial performance gains over optimized cacheless MU-MIMO systems. For example, with 32 transmit antennas and 2 receive antennas per user, VCC yields throughput improvements exceeding 300%. These gains are further amplified under imperfect CSI at the transmitter, where VCC’s ability to offload interference mitigation to the receivers ensures robust performance even in the face of degraded CSI quality and elevated acquisition costs.

The interference exploitation precoding (IEP) leverages the harmful interference to align at the constructive interference (CI) region via symbol level precoding (SLP), which greatly improves the conventional zero forcing precoding with QPSK modulation or even higher modulations. This letter firstly develops a joint phase rotation structure, considering both the outer phase rotation for multiple layers and the inner phase alignment for IEP with finite block length in multi-user multiple-input multiple-output (MU-MIMO) systems, termed as JPR-IEP. To tackle the problem, a decoupling scheme is presented, which breaks JPR-IEP into two independent steps as DPR-IEP, thus converting the non-convex JPR-IEP to a solvable problem with low complexity. At last, a codebook-assisted DPR-IEP, namely CB-DPR-IEP with less computational complexity and feed-forward overhead is further investigated, which is approved to be the optimal choice considering the performance, the feed-forward and the complexity for practical MU-MIMO systems.

Applying Nakagami distribution for BER analysis of equal gain transmission in MU-MIMO systems

In this paper, we consider the precoder design for an underloaded or critically loaded downlink multi-user multiple-input multiple-output (MIMO) communication system. We propose novel precoding and decoding schemes which enhance system performance based on rate splitting at the transmitter and single-stage successive interference cancellation at the receivers. The proposed successive null-space (SNS) precoding utilizes linear combinations of the null-space basis vectors of the successively augmented MIMO channel matrices of the users as precoding vectors to adjust the inter-user-interference experienced by the receivers. We formulate a non-convex weighted sum rate optimization problem for the precoding vectors and the associated power allocation for the proposed SNS-based MIMO-rate-splitting multiple access (RSMA) scheme. We obtain a suboptimal solution for this problem via successive convex approximation. Moreover, we study the robustness of the proposed precoding scheme to imperfect channel state information (CSI) at the base station via derivative-based sensitivity analysis. Our analysis and simulation results reveal the enhanced performance and robustness of the proposed SNS-based MIMO-RSMA scheme over several baseline multi-user MIMO schemes, especially for imperfect CSI.

This paper investigates a time-division multiuser multiple-input multiple-output (MIMO) antenna system in K-block flat fading where users are given individual outage rate probability constraints and only one user accesses the channel at any given time slot (or block). Assuming a downlink channel and that the transmitter knows only the statistical information about the channel, our aim is to minimize the overall transmit power for achieving the users' outage constraint by jointly optimizing the power allocation and the time-sharing (i.e., the number of time slots) of the users. This paper first derives the so-called minimum power equation (MPE) to solve for the minimum transmit power required for attaining a given outage rate probability of a single-user MIMO block-fading channel if the number of blocks is predetermined. We then construct a convex optimization problem, which can mimic the original problem structure and permits to jointly consider the power consumption and the probability constraints of the users, to give a suboptimal multiuser time-sharing solution. This is finally combined with the MPE to provide a joint power allocation and time-sharing solution for the time-division multiuser MIMO system. Numerical results demonstrate that the proposed scheme performs nearly the same as the global optimum with inappreciable difference.

In multi-user millimeter wave (mmWave) multiple input multiple output (MIMO) systems, obtaining accurate information/knowledge regarding the channel state is crucial to achieving multi-user interference cancellation and reliable beamforming (BF)–to compensate for severe path loss. This knowledge is nonetheless very challenging to acquire in practice since large antenna arrays experience a low signal-to-noise ratio (SNR) before BF. In this paper, a multi-user channel estimation (CE) scheme namely generalized-block compressed sampling matching pursuit (G-BCoSaMP), is proposed for multi-user mmWave MIMO systems over frequency selective fading channels. This scheme exploits the cluster-structured sparsity in the angular and delay domain of mmWave channels determined by the actual spatial frequencies of each path. As the corresponding spatial frequencies of multi-user mmWave MIMO systems with Hybrid BF often fall between the discrete Fourier transform (DFT) bins due to the continuous Angle of Arrival (AoA)/Angle of Departure (AoD), the proposed G-BCoSaMP algorithm can address the resulting power leakage problem. Simulation results show that the proposed algorithm is effective and offer a better CE performance in terms of MSE when compared to the generalized block orthogonal matching pursuit (G-BOMP) algorithm that does not possess a pruning step.

This paper considers the joint linear transceiver design problem for the downlink multiuser multiple-input-multiple-output (MIMO) systems with coordinated base stations (BSs). We consider maximization of the weighted sum rate with per BS antenna power constraint problem. We propose novel centralized and computationally efficient distributed iterative algorithms that achieve local optimum to the latter problem. These algorithms are described as follows. First, by introducing additional optimization variables, we reformulate the original problem into a new problem. Second, for the given precoder matrices of all users, the optimal receivers are computed using minimum mean-square-error (MMSE) method and the optimal introduced variables are obtained in closed form expressions. Third, by keeping the introduced variables and receivers constant, the precoder matrices of all users are optimized by using second-order-cone programming (SOCP) and matrix fractional minimization approaches for the centralized and distributed algorithms, respectively. Finally, the second and third steps are repeated until these algorithms converge. We have shown that the proposed algorithms are guaranteed to converge. We also show that the proposed algorithms require less computational cost than that of the existing linear algorithm. All simulation results demonstrate that our distributed algorithm achieves the same performance as that of the centralized algorithm. Moreover, the proposed algorithms outperform the existing linear algorithm. In particular, when each of the users has single antenna, we have observed that the proposed algorithms achieve the global optimum.

In a multiuser multiple-input multiple-output (MU-MIMO) downlink system, users are susceptible to interuser interference (IUI) because of data being simultaneously transmitted over the same time-frequency resources. Conventionally, precoding algorithms aim to eliminate the IUI. However, constructive interference (CI) precoding can achieve better error performance by exploiting the IUI. This article presents a high-throughput CI precoder. Design optimization across the algorithm and the architecture layers is conducted, reducing the complexity for multiplications by 81.6%. As the number of iterations for convergence varies, dynamic resource allocation is utilized to support each modulation mode with maximized utilization: time-multiplexing for the 4-QAM mode and parallel-processing for the 16-QAM mode. The proposed symbol updater also allows more efficient scheduling. As a proof of concept, a CI precoder chip that supports up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$16 \times $ </tex-math></inline-formula> MU-MIMO systems is designed based in a 40-nm CMOS technology. The performance gains at a bit error rate (BER) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$= 10^{-4}$ </tex-math></inline-formula> are 10.7 and 12.5 dB for 4-QAM and 16-QAM, respectively, compared with conventional regularized zero-forcing (RZF) schemes. The precoder delivers a maximum throughput of 3.2 Gb/s at a clock frequency of 200 MHz for the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$16 \times $ </tex-math></inline-formula> MU-MIMO configuration.