Spectral Efficiency Maximization of a Single Cell Massive MU-MIMO Down-Link TDD System by Appropriate Resource Allocation

This paper deals with the problem of maximizing the spectral efficiency in a massive multi-user MIMO downlink system, where a base station is equipped with a very large number of antennas and serves single-antenna users simultaneously in the same frequency band, and the beamforming training scheme is employed in the time-division duplex mode. An optimal resource allocation that jointly selects the training duration on uplink transmission, the training signal power on downlink transmission, the training signal power on uplink transmission, and the data signal power on downlink transmission is proposed in such a way that the spectral efficiency is maximized given the total energy budget. Since the spectral efficiency is the main concern of this work, and its calculation using the lower bound on the achievable rate is computationally very intensive, in this paper, we also derive approximate expressions for the lower bound of achievable downlink rate for the maximum ratio transmission (MRT) and zero-forcing (ZF) precoders. The computational simplicity and accuracy of the approximate expressions for the lower bound of achievable downlink rate are validated through simulations. By employing these approximate expressions, experiments are conducted to obtain the spectral efficiency of the massive MIMO downlink time-division duplexing system with the optimal resource allocation and that of the beamforming training scheme. It is shown that the spectral efficiency of the former system using the optimal resource allocation is superior to that yielded by the latter scheme in the cases of both MRT and ZF precoders

Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolution

MIMO processing plays a central part towards the recent increase in spectral and energy efficiencies of wireless networks. MIMO has grown beyond the original point-to-point channel and nowadays refers to a diverse range of centralized and distributed deployments. The fundamental bottleneck towards enormous spectral and energy efficiency benefits in multiuser MIMO networks lies in a huge demand for accurate channel state information at the transmitter (CSIT). This has become increasingly difficult to satisfy due to the increasing number of antennas and access points in next generation wireless networks relying on dense heterogeneous networks and transmitters equipped with a large number of antennas. CSIT inaccuracy results in a multi-user interference problem that is the primary bottleneck of MIMO wireless networks. Looking backward, the problem has been to strive to apply techniques designed for perfect CSIT to scenarios with imperfect CSIT. In this paper, we depart from this conventional approach and introduce the readers to a promising strategy based on rate-splitting. Rate-splitting relies on the transmission of common and private messages and is shown to provide significant benefits in terms of spectral and energy efficiencies, reliability and CSI feedback overhead reduction over conventional strategies used in LTE-A and exclusively relying on private message transmissions. Open problems, impact on standard specifications and operational challenges are also discussed.Comment: accepted to IEEE Communication Magazine, special issue on LTE Evolutio

Resource Allocation in Collocated Massive MIMO for 5G and Beyond

Massive multiuser multiple-input multiple-output (MIMO) systems have been recently introduced as a promising technology for the next generation of wireless networks. It has been proven that linear precoders/detectors such as maximum ratio transmitting/maximum ratio combining (MRT/MRC), zero forcing (ZF), and linear minimum mean square error (LMMSE) on the downlink (DL)/uplink (UL) transmission can provide near optimal performance in such systems. Acquiring channel state information (CSI) at the transmitter as well as the receiver is one of the challenges in multiuser massive MIMO that can affect the network performance. Any data transmission in multiuser massive MIMO systems starts with the user transmitting UL pilots. The base station (BS) then uses the MMSE estimation method to accurately estimate the CSI from the pilot sequences. Since the UL and DL channels are reciprocal in time division duplex (TDD) mode, the BS employs the obtained CSI to precode the data symbols prior to DL transmission. The users also need the CSI knowledge to accurately decode the DL signals. Beamforming training (BT) scheme is one of the methods that is proposed in the literature to provide the CSI knowledge for the users. In this scheme, the BS precodes and transmits a pilot sequence to the users such that each user can estimate its effective channel coefficients. Developing an optimal resource distribution method that enhances the system performance is another challenging issue in multiuser massive MIMO. As mentioned earlier, CSI acquisition is one of the requirements of multiuser massive MIMO, and UL pilot transmission is the common method to achieve that. Conventionally, equal powers have been considered for the pilot transmission phase and data transmission phase. However, it can be shown that the performance of the system under this method of power distribution is not optimal. Therefore, to further improve the performance of multiuser massive MIMO technology, especially in cases where the antenna elements are not well separated and the propagational dispersion is low, optimal resource allocation is required. Hence, the main objective of this M.A.Sc. thesis is to develop an optimal resource allocation among pilot and data symbols to maximize the spectral efficiency, assuming different receivers such as MRC, ZF, and LMMSE are employed at the BS. Since the calculation of spectral efficiency using the lower bound on the achievable rate is computationally very intensive, we first obtain closed-form expressions for the achievable UL rate of users, assuming the angular domain in the physical channel model is divided into a finite number of separate directions. An approximate expression for spectral efficiency is then developed using the aforementioned closed-form rates. Finally, we propose a resource allocation scheme in which the pilot power, data power, and training duration are optimally chosen in order to maximize the spectral efficiency in a given total power budget. Extensive simulations are conducted in MATLAB and the results are presented that illustrate the notable improvement in the achievable spectral efficiency through the proposed power allocation scheme. Moreover, the results show that the performance of the proposed method is much superior when the number of channel directions or the number of antennas at BS increases. Furthermore, while the advantage of the proposed method is more notable in the case of ZF and LMMSE receivers, it still outperforms the equal power allocation method for the MRC receiver in terms of spectral efficiency

Low-Complexity Multi-User MIMO Algorithms for mmWave WLANs

Very high throughput and high-efficiency wireless local area networks (WLANs) have become essential for today's significant global Internet traffic and the expected significant global increase of public WiFi hotspots. Total Internet traffic is predicted to expand 3.7-fold from 2017 to 2022. In 2017, 53% of overall Internet traffic used by WiFi networks, and that number is expected to increase to 56.8% by 2022. Furthermore, 80% of overall Internet traffic is expected to be video traffic by 2022, up from 70% in 2017. WiFi networks are also expected to move towards denser deployment scenarios, such as stadiums, large office buildings, and airports, with very high data rate applications, such as ultra-high definition video wireless streaming. Thus, in order to meet the predicted growth of wireless traffic and the number of WiFi networks in the world, an efficient Internet access solution is required for the current IEEE 802.11 standards. Millimeter wave (mmWave) communication technology is expected to play a crucial role in future wireless networks with large user populations because of the large spectrum band it can provide. To further improve spectrum efficiency over mmWave bands in WLANs with large numbers of users, the IEEE 802.11ay standard was developed from the traditional IEEE 802.11ad standard, aiming to support multi-user MIMO. Propagation challenges associated with mmWave bands necessitate the use of analog beamforming (BF) technologies that employ directional transmissions to determine the optimal sector beam between a transmitter and a receiver. However, the multi-user MIMO is not exploited, since analog BF is limited to a single-user, single-transmission. The computational complexity of achieving traditional multi-user MIMO BF methods, such as full digital BF, in the mmWave systems becomes significant due to the hardware constraints. Our research focuses on how to effectively and efficiently realize multi-user MIMO transmission to improve spectrum efficiency over the IEEE 802.11ay mmWave band system while also resolving the computational complexity challenges for achieving a multi-user MIMO in mmWave systems. This thesis focuses on MAC protocol algorithms and analysis of the IEEE 802.11ay mmWave WLANs to provide multi-user MIMO support in various scenarios to improve the spectrum efficiency and system throughput. Specifically, from a downlink single-hop scenario perspective, a VG algorithm is proposed to schedule simultaneous downlink transmission links while mitigating the multi-user interference with no additional computational complexity. From a downlink multi-hop scenario perspective, a low-complexity MHVG algorithm is conducted to realize simultaneous transmissions and improve the network performance by taking advantage of the spatial reuse in a dense network. The proposed MHVG algorithm permits simultaneous links scheduling and mitigates both the multi-user interference and co-channel interference based only on analog BF information, without the necessity for feedback overhead, such as channel state information (CSI). From an uplink scenario perspective, a low-complexity user selection algorithm, HBF-VG, incorporates user selection with the HBF algorithm to achieve simultaneous uplink transmissions for IEEE 802.11ay mmWave WLANs. With the HBF-VG algorithm, the users can be selected based on an orthogonality criterion instead of collecting CSI from all potential users. We optimize the digital BF to mitigate the residual interference among selected users. Extensive analytical and simulation evaluations are provided to validate the performance of the proposed algorithms with respect to average throughput per time slot, average network throughput, average sum-rate, energy efficiency, signal-to-interference-plus-noise ratio (SINR), and spatial multiplexing gain

Evolution Toward 5G Mobile Networks - A Survey on Enabling Technologies

In this paper, an extensive review has been carried out on the trends of existing as well as proposed potential enabling technologies that are expected to shape the fifth generation (5G) mobile wireless networks. Based on the classification of the trends, we develop a 5G network architectural evolution framework that comprises three evolutionary directions, namely, (1) radio access network node and performance enabler, (2) network control programming platform, and (3) backhaul network platform and synchronization. In (1), we discuss node classification including low power nodes in emerging machine-type communications, and network capacity enablers, e.g., millimeter wave communications and massive multiple-input multiple-output. In (2), both logically distributed cell/device-centric platforms, and logically centralized conventional/wireless software defined networking control programming approaches are discussed. In (3), backhaul networks and network synchronization are discussed. A comparative analysis for each direction as well as future evolutionary directions and challenges toward 5G networks are discussed. This survey will be helpful for further research exploitations and network operators for a smooth evolution of their existing networks toward 5G networks

Spectral Efficiency Maximization of a Massive Multiuser MIMO System via Appropriate Power Allocation

Massive multiuser multiple-input multiple-output (MU-MIMO) systems are being considered for the next generation wireless networks in view of their ability to increase both the spectral and energy efficiencies. For such systems, linear detectors such as zero-forcing (ZF) and maximum-ratio combining (MRC) detectors on the uplink (UL) transmission have been shown to provide near optimal performance. As well, linear precoders such as ZF and maximum-ratio transmission (MRT) precoders on the downlink (DL) transmission offer lower complexity along with a near optimal performance in these systems. One of the most challenging problems in massive MU-MIMO systems is obtaining the channel state information (CSI) at the transmitter as well as the receiver. In such systems, the base station (BS) obtains CSI using pilot sequences, which are transmitted by the users. Due to the channel reciprocity between the UL and DL channels in the time-division duplex (TDD) mode, BS employs CSI obtained to precode the data symbols in DL transmission. To accurately decode the received symbols in the DL transmission, the users also need to acquire CSI. In view of this, a beamforming training (BT) scheme has been proposed in the literature to obtain the estimates of CSI at each user. In this scheme, BS transmits a short pilot sequence to the users in a way such that each user estimates the effective channel gain. Conventionally, the power of the pilot symbols has been considered equal to the power of data symbols for all the users. In this thesis, we pose and answer a basic question about the operation of a base station: How much the spectral efficiency could be improved if the transmit power allocated to the pilot and data symbols of each user are chosen in some optimal fashion? In answering this question and in order to maximize the spectral efficiency for a given total energy budget, some methods of power allocation are proposed. First, we derive a closed-form approximate expression for the achievable downlink rate for the maximum ratio transmission precoder based on small-scale fading in order to evaluate the spectral efficiency in the BT scheme. Then, we propose three methods of power allocation in order to maximize the spectral efficiency for a given total power budget among the users. In the first proposed method, we allocate equal pilot power as well as equal data power for all users in order to maximize the spectral efficiency. In the second proposed method, we allow for the allocation of different data powers among the users, whereas the pilot power for each user is kept the same and is specified. In the third method, we optimally allocate equal pilot power and a different data power for each user in such a way that the spectral efficiency is maximized. Numerical results are obtained showing that all the three proposed methods are superior to the existing methods in terms of spectral efficiency. In addition, they also show that the third proposed method of power allocation outperforms the other two proposed methods in terms of the spectral efficiency. Next, we derive a closed-form approximate expression for the achievable downlink rate for the maximum ratio transmission precoder based on large-scale fading in order to evaluate the spectral efficiency in the BT scheme. Then, we propose four methods of power allocation in order to maximize the spectral efficiency for a given total power budget among the users. In the first method, power is allocated among the pilot and data symbols in such a way that the pilot power as well as the data power for each user is the same. In the second method, power is allocated among the data symbols of the various users, whereas the pilot power for each user is the same and is specified. In this method, the data power for each user is optimally determined to maximize the spectral efficiency. In the third method, power is allocated among the pilot and data symbols of the various users, whereas the pilot power for each user is the same but determined. In this method, the same pilot power along with the various data powers is optimized to maximize the spectral efficiency. Finally, in the fourth method, power is allocated optimally among each of the pilot and data symbols of the various users so as to maximize the spectral efficiency. Numerical results are obtained showing that the performance of the first proposed method is approximately the same as that of the conventional approach. In addition, they also show that the second, third and fourth methods of power allocation yield similar performance in terms of spectral efficiency, and that the spectral efficiency of these methods is much superior to that of the first method or of the conventional method. Finally, we investigate the spectral efficiency of massive MU-MIMO systems on an UL transmission with a very large number of antennas at the base station serving single-antenna users. A practical physical channel model is proposed by dividing the angular domain into a finite number of distinct directions. A lower bound on the achievable rate of the uplink data transmission is derived using a linear detector for each user and employed in defining the spectral efficiency. The lower bound obtained is further modified for the maximum-ratio combining and zero-forcing receivers. A power control scheme based on the large-scale fading is also proposed to maximize the spectral efficiency under the peak power constraint. Experiments are conducted to evaluate the lower bounds obtained and the performance of the proposed method. The numerical results show that the proposed power control method provides a spectral efficiency which is the same as that of the maximum power criterion using the ZF receiver. Further, the proposed method provides a spectral efficiency that is higher than that provided by the maximum power criterion using the MRC receiver

Cooperative Transmission for Downlink Distributed Antenna in Time Division Duplex System

Multi-user distributed antenna system (MU-DAS) systems play the essential role in improving throughput performance in wireless communications. This improvement can be achieved by exploiting the spatial domain and without the need of additional power and bandwidth. In this thesis, three main issues which are of importance to the data rate transmission have been investigated. Firstly, user clustering in MU-DAS downlink systems has been considered, where this technique can be effciently used to reduce the complexity and cost caused by radio frequency chains, associated with antennas while keeping most of the diversity advantages of the system. The proposed user clustering algorithm which can select an optimal set of antennas for transmission. The capacity achieved by the proposed algorithm is almost same as the capacity of the optimum search method, with much lower complexity. Secondly, interference alignment in MU-DAS downlink systems has been studied. The inter-cluster interference is uncoordinated and limits the system performance. The inter-cluster interference should be eliminated or minimized carefully. The interference alignment is proposed to consolidate the strong inter-cluster interference into smaller dimensions of signal space at each user and use the remaining dimensions to transmit the desired signals without any interference. The performance of single cluster is better than the proposed algorithm due to the absence of intercluster interference in the single cluster. The numerical shows that the proposed algorithm is more suitable in multi-cell DAS environment due to the presence of inter-cell interference. Finally, the impact of different user mobility on TDD downlink MUDAS has been studied. The downlink data transmission in time division duplex (TDD) systems is optimized according to the channel state information (CSI) which is obtained at the uplink time slot. However, the actual channel at downlink time slot may be different from the estimated channel due to channel variation in mobility environment. Based on mobility state information (MSI), an autocorrelation based feedback interval adjustment technique is proposed. The proposed technique adjusts the CSI update interval and mitigates the performance degradation imposed by the user mobility and the transmission delay. Cooperative clusters are formed to maximize sum rate. In order to reduce the computational complexity, a channel gain based antenna selection and signal-to-interference plus noise ratio (SINR) based user clustering are developed. A downlink ergodic capacity is derived in single user clustering. The derived analytical expressions of the downlink ergodic capacity are verified by system simulations. Numerical results show that the proposed scheme can improved sum rate over the non cooperative system and no MSI knowledge. The proposed technique has good performance for a wide range of user speed and suitable for future wireless communications systems

Joint precoding and antenna selection in massive mimo systems

This thesis presents an overview of massive multiple-input multiple-output (MIMO) systems and proposes new algorithms to jointly precode and select the antennas. Massive MIMO is a new technology, which is candidate for comprising the fifth-generation (5G) of mobile cellular systems. This technology employs a huge amount of antennas at the base station and can reach high data rates under favorable, or asymptotically favorable, propagation conditions, while using simple linear processing. However, massive MIMO systems have some drawbacks, such as the high cost related to the base stations. A way to deal with this issue is to employ antenna selection algorithms at the base stations. These algorithms reduce the number of active antennas, decreasing the deployment and maintenance costs related to the base stations. Moreover, this thesis also describes a class of nonlinear precoders that are rarely addressed in the literature; these techniques are able to generate precoded sparse signals in order to achieve joint precoding and antenna selection. This thesis proposes two precoders belonging to this class, where the number of selected antennas is controlled by a design parameter. Simulation results show that the proposed precoders reach a lower bit-error rate than the classical antenna selection algorithms. Furthermore, simulation results show that the proposed precoders present a linear relation between the aforementioned design parameter that controls the signals’ sparsity and the number of selected antennas. Such relation is invariant to the number of base station’s antennas and the number of terminals served by this base station.Esta dissertação apresenta uma visão geral sobre MIMO (do termo em inglês, multiple-input multiple-output) massivo e propõe novos algoritmos que permitem a pré-codificacão de sinais e a seleção de antenas de forma simultânea. MIMO massivo é uma nova tecnologia candidata para compor a quinta geração (5G) dos sistemas celulares. Essa tecnologia utiliza uma quantidade muito grande de antenas na estação-base e, sob condições de propagação favorável ou assintoticamente favorável, pode alcançar taxas de transmissão elevadas, ainda que utilizando um simples processamento linear. Entretanto, os sistemas MIMO massivo apresentam algumas desvantagens, como por exemplo, o alto custo de implementação das estações-bases. Uma maneira de lidar com esse problema é utilizar algoritmos de seleção de antenas na estação-base. Com esses algoritmos é possível reduzir o número de antenas ativas e consequentemente reduzir o custo nas estações-bases. Essa dissertação também apresenta uma classe pouco estudada de pré-codificadores não-lineares que buscam sinais pré-codificados esparsos para realizar a seleção de antenas conjuntamente com a pré-codificação. Além disso, este trabalho propõem dois novos pré-codificadores pertencentes a essa classe, para os quais o número de antenas selecionadas é controlado por um parâmetro de projeto. Resultados de simulações mostram que os pré-codificadores propostos conseguem uma BER (do termo em inglês, bit-error rate) menor que os algoritmos clássicos usados para selecionar antenas. Além disso, resultados de simulações mostram que os pré-codificadores propostos apresentam uma relação linear com o parâmetro de projeto que controla a quantidade de antenas selecionadas; tal relação independe do número de antenas na estação-base e do número de terminais servidos por essa estação