On the Throughput of Large-but-Finite MIMO Networks using Schedulers

This paper studies the sum throughput of the {multi-user} multiple-input-single-output (MISO) networks in the cases with large but finite number of transmit antennas and users. Considering continuous and bursty communication scenarios with different users' data request probabilities, we derive quasi-closed-form expressions for the maximum achievable throughput of the networks using optimal schedulers. The results are obtained in various cases with different levels of interference cancellation. Also, we develop an efficient scheduling scheme using genetic algorithms (GAs), and evaluate the effect of different parameters, such as channel/precoding models, number of antennas/users, scheduling costs and power amplifiers' efficiency, on the system performance. Finally, we use the recent results on the achievable rates of finite block-length codes to analyze the system performance in the cases with short packets. As demonstrated, the proposed GA-based scheduler reaches (almost) the same throughput as in the exhaustive search-based optimal scheduler, with substantially less implementation complexity. Moreover, the power amplifiers' inefficiency and the scheduling delay affect the performance of the scheduling-based systems significantly

Multi-Antenna Techniques for Next Generation Cellular Communications

Future cellular communications are expected to offer substantial improvements for the pre- existing mobile services with higher data rates and lower latency as well as pioneer new types of applications that must comply with strict demands from a wider range of user types. All of these tasks require utmost efficiency in the use of spectral resources. Deploying multiple antennas introduces an additional signal dimension to wireless data transmissions, which provides a significant alternative solution against the plateauing capacity issue of the limited available spectrum. Multi-antenna techniques and the associated key enabling technologies possess unquestionable potential to play a key role in the evolution of next generation cellular systems. Spectral efficiency can be improved on downlink by concurrently serving multiple users with high-rate data connections on shared resources. In this thesis optimized multi-user multi-input multi-output (MIMO) transmissions are investigated on downlink from both filter design and resource allocation/assignment points of view. Regarding filter design, a joint baseband processing method is proposed specifically for high signal-to-noise ratio (SNR) conditions, where the necessary signaling overhead can be compensated for. Regarding resource scheduling, greedy- and genetic-based algorithms are proposed that demand lower complexity with large number of resource blocks relative to prior implementations. Channel estimation techniques are investigated for massive MIMO technology. In case of channel reciprocity, this thesis proposes an overhead reduction scheme for the signaling of user channel state information (CSI) feedback during a relative antenna calibration. In addition, a multi-cell coordination method is proposed for subspace-based blind estimators on uplink, which can be implicitly translated to downlink CSI in the presence of ideal reciprocity. Regarding non-reciprocal channels, a novel estimation technique is proposed based on reconstructing full downlink CSI from a select number of dominant propagation paths. The proposed method offers drastic compressions in user feedback reports and requires much simpler downlink training processes. Full-duplex technology can provide up to twice the spectral efficiency of conventional resource divisions. This thesis considers a full-duplex two-hop link with a MIMO relay and investigates mitigation techniques against the inherent loop-interference. Spatial-domain suppression schemes are developed for the optimization of full-duplex MIMO relaying in a coverage extension scenario on downlink. The proposed methods are demonstrated to generate data rates that closely approximate their global bounds

Operating multi-user transmission for 5G and beyond cellular systems

Every decade, a new generation of cellular networks is released to keep up with the ever-growing demand for data and use cases. Traditionally, cellular networks rely on partitioning radio resources into a set of physical resource blocks (PRBs). Each PRB is used by the base-station to transmit exclusively to one user, which is referred to as single-user transmission. Recently, multi-user transmission has been introduced to enable the base-station to simultaneously serve multiple users using the same PRB. While multi-user transmission can be much more efficient than its single-user counterpart, it is significantly more challenging to operate. Thus, in this thesis we study the operation, i.e., the Radio Resource Management (RRM), for two popular multi-user transmission technologies; namely, 1) Non-Orthogonal Multiple Access (NOMA) and 2) Multi-User Multiple-Input Multiple-Output (MU-MIMO). For NOMA RRM, we study a multi-cell, multi-carrier downlink system. First, we formulate and solve a centralized proportional fair scheduling genie problem that jointly performs user selection, power allocation and power distribution, and Modulation and Coding Scheme (MCS) selection. While such a centralized schedule is practically infeasible, it upper bounds the achievable performance. Then, we propose a simple static coordinated power allocation scheme across all cells for NOMA using a simple power map that is easily calibrated offline. We find that using a simple static coordinated power allocation scheme improves performance by 80% compared to equal power allocation. Finally, we focus on online network operation and study practical schedulers that perform user-selection, power distribution, and MCS selection. We propose a family of practical scheduling algorithms, each of them exhibiting a different trade-off between complexity (i.e., run-time) and performance. The one we selected sacrifices a maximum of 10% performance while reducing the computation time by a factor of 45 with respect to the optimal user scheduler. For MU-MIMO RRM, we focus on the study of the downlink of an OFDMA massive MU-MIMO single cell assuming ZFT (Zero Forcing Transmission) precoding. An offline study is initiated with the goal of finding the best achievable performance by jointly optimizing user-selection, power distribution and MCS selection. The best performance is analyzed by using both Branch-Reduce-and-Bound (BRB) global optimization technique for upper-bounding the achievable performance and a set of different greedy searches for lower bounding the achievable performance to find good feasible solutions. The results suggest that a specific search strategy referred to as greedy-down-all-the-way (GDAW) with full-drop (FD) is quasi-optimal. Afterwards, we design a simple practical scheduler that achieves 97% of the performance to GDAW with FD and has comparable runtime to that of the state-of-the-art benchmark that selects all users, performs ZFT precoding followed by power distribution using water-filling. The proposed scheme performs a simple round robin grouping to select users, followed by ZFT precoding and joint power distribution and MCS selection via a novel greedy algorithm with a possible additional iteration to take zero-rate users into account. Our solution outperforms the benchmark by 281%

Energy-aware resource allocation in next generation wireless networks : application in large-scale MIMO Systems

In this thesis, we investigate the resource allocation problem for wireless networks that incorporate large-scale multiple-input multiple-output (MIMO) systems. These systems are considered as key technologies for future 5G wireless networks and are based on using few hundreds of antennas simultaneously to serve tens of users in the same time-frequency resource. The gains obtained by large-scale MIMO systems cannot be fully exploited without adequate resource allocation strategies. Hence, the aim of this thesis is to develop energy-aware resource allocation solutions for large-scale MIMO systems that take into consideration network power cost. Firstly, this thesis investigates the downlink of a base station equipped with large-scale MIMO system while taking into account a non-negligible transmit circuit power consumption. This consumption involves that activating all RF chains does not always necessarily achieve the maximum sum-rate. Thus, we derive the optimal number of activated RF chains. In addition, efficient antenna selection, user scheduling and power allocation algorithms in term of instantaneous sum-rate are proposed and compared. Also, fairness is investigated by considering equal receive power among users. Secondly, this thesis investigates a large-scale MIMO system that incorporates energy harvesting that is a promising key technology for greening future wireless networks since it reduces network operation costs and carbon footprints. Hence, we consider distributed large-scale MIMO systems made up of a set of remote radio heads (RRHs), each of which is powered by both an independent energy harvesting source and the grid. The grid energy source allows to compensate for the randomness and intermittency of the harvested energy. Optimal on-line and off-line energy management strategies are developed. In addition, on-line energy management algorithm based on energy prediction is devised. The feasibility problem is addressed by proposing an efficient link removal algorithm and for better energy efficiency, RRH on/off operation is investigated. Thirdly, wireless backhauling was proposed as an alternative solution that enable low-cost connection between the small base stations and the macro base station in heterogeneous networks (HetNets). The coexistence of massive MIMO, HetNets and wireless backhauling is a promising research direction since massive MIMO is a suitable solution to enable wireless backhauling. Thus, we propose a new transmission technique that is able to efficiently manage the interference in heterogeneous networks with massive MIMO wireless backhaul. The optimal time splitting parameter and the allocated transmit power are derived. The proposed transmission technique is shown to be more efficient in terms of transmit power consumption than the conventional reverse time division duplex with bandwidth splitting. In this thesis, we developed efficient resource allocation solutions related to system power for wireless networks that incorporate large-scale MIMO systems under different assumptions and network architectures. The results in this thesis can be expanded by investigating the research problems given at the end of the dissertation

Alocação de recursos para sistemas móveis multi-utilizador e multi-antena

Doutoramento em Engenharia ElectrotécnicaThe thesis addresses the sum rate or spectral e ciency maximization problem in cellular systems with two main components, multiple antennas and multiple users. In order to solve such a problem, several resource allocation techniques are studied and developed for di erent cellular scenarios. The antennas at the transmitters are arranged in several con gurations, i.e., co-located or distributed and for such arrangements di erent levels of coordination and cooperation between transmitters are investigated. Accounting for more receiver antennas than transmitter antennas implies that system optimization must select the best transmitter-receiver match (combinatorial problem) which can be solved with di erent degrees of cooperation between transmitters. The system models studied can be classi ed either as interference limited or as power limited systems. In interference limited systems the resource allocation is carried out independently by each transmitter which yield power leakage to unintended receivers. For this kind of systems, the access network using distributed antenna architectures is examined. The properties of distributed antenna in cellular systems as well as the gains they provide in terms of frequency reuse and throughput are assessed. Accounting for multiple user scenarios, several techniques and algorithms for transmitter-receiver assignment, power allocation, and rate allocation are developed in order to maximize the spectral e ciency. In power limited systems the transmitters jointly allocate resources among transmit and receive antennas. The transmitters are equipped with multiple antennas and signal processing is implemented in order to suppress inter-user interference. Single-cell and multi-cell systems are studied and the problem of sum rate maximization is tackled by decoupling the user selection and the resource allocation (power and precoding) processes. The user selection is a function of the type of precoding technique that is implemented and the level of information that can be processed at the transmitter. The developed user selection algorithms exploit information provided by novel channel metrics which establish the spatial compatibility between users. Each metric provides a di erent trade-o between the accuracy to identify compatible users, and the complexity required to compute it. Numerical simulations are used to assess the performance of the proposed user selection techniques (metrics and algorithms) whose performance are compared to state-of-the-art techniques.Esta tese descreve o problema da maximização da taxa de transmissão ou e ciência espectral em sistemas moveis tomando em atenção duas características fundamentais destes, o número de antenas e utilizadores. A fim de resolver este tipo de problema, várias técnicas de alocação de recursos foram estudadas e propostas para diferentes cenários. As antenas nos transmissores estão organizadas em diferentes configurações, podendo ser localizadas ou distribuídas e para estes esquemas, diferentes níveis de cooperação e coordenação entre transmissores foram investigados. Assumindo mais antenas receptoras do que antenas transmissoras, implica que a otimização do sistema seleccione as melhores combinações de transmissor-receptor (problema combinatório), o que pode ser concretizado usando diferentes graus de cooperação entre transmissores. Os modelos de sistemas estudados, podem ser classificados como sistemas limitados por interferência ou sistemas limitados por potência. Em sistemas limitados por interferência a alocação de recursos e feita independentemente para cada transmissor o que resulta em perda de energia para os receptores não tomados em consideração. Para este tipo de sistemas, e considerado o caso em que a rede de acesso e constituída por antenas distribuídas. Os ganhos obtidos devido ao uso de antenas distribuídas, quer em termos do planeamento de frequências quer da maximização da taxa de transmissão são considerados. Assumindo esquemas multi-utilizador, várias técnicas e algoritmos de transmissão-recepção, alocação de potência e de taxa de transmissão foram desenvolvidos para maximizar a e ciência espectral. Para sistemas limitados em potência os transmissores alocam os recursos quer de antenas de transmissão quer de recepção conjuntamente. Os transmissores estão equipados com várias antenas e o processamento de sinal e implementado de modo a eliminar a interferência entre utilizadores. Sistemas de célula única e de múltiplas células foram estudados. Para estes foi considerado o problema da maximização de taxa de transmissão o qual foi resolvido heuristicamente, através do desacoplamento do problema em duas partes, uma onde se efectua a seleção de utilizadores e outra onde se considera a alocação de recursos. A seleção de utilizadores e feita em função do tipo de técnicas de pré-codificação implementadas e do nível de informação que o transmissor possui. Os algoritmos de seleção de utilizadores desenvolvidos verificam a compatibilidade espacial entre utilizadores, usando para tal métricas propostas. Cada uma das métricas oferece um trade-off diferente entre a precisão para identificar um utilizador compatível e a complexidade necessária para a implementar. Foram usadas simulações numéricas para avaliar a performance das técnicas de seleção de utilizadores propostas (métricas e algoritmos), performance que foi comparada com as técnicas mais inovadoras

Resource Allocation for Coordinated Multipoint Joint Transmission System and Received Signal Strength Based Positioning in Long Term Evolution Network

The Long-Term Evolution Advanced (LTE-A) system are expected to provide high speed and high quality services, which are supported by emerging technologies such as Coordinated Multipoint (CoMP) transmission and reception. Dynamic resource allocation plays a vital role in LTE-A design and planning, which is investigated in this thesis. In addition, Received Signal Strength (RSS) based positioning is also investigated in orthogonal frequency division multiplexing (OFDM) based wireless networks, which is based on an industry project. In the first contribution, a physical resource blocks (PRB) allocation scheme with fuzzy logic based user selection is proposed. This work considers three parameters and exploit a fuzzy logic (FL) based criterion to categorize users. As a result, it enhances accuracy of user classification. This work improves system capacity by a ranking based PRBs allocation schemes. Simulation results show that proposed fuzzy logic based user selection scheme improves performance for CoMP users. Proposed ranking based greedy allocation algorithm cut complexity in half but maintain same performance. In the second contribution, a two-layer proportional-fair (PF) user scheduling scheme is proposed. This work focused on fairness between CoMP and Non-CoMP users instead of balancing fairness in each user categories. Proposed scheme jointly optimizes fairness and system capacity over both CoMP and Non-CoMP users. Simulation results show that proposed algorithm significantly improves fairness between CoMP and Non-CoMP users. In the last contribution, RSS measurement method in LTE system is analyzed and a realizable RSS measurement method is proposed to fight against multipath effect. Simulation results shows that proposed method significantly reduced measurement error caused by multipath. In RSS based positioning area, this is the first work that consider exploiting LTE’s own signal strength measurement mechanism to enhance accuracy of positioning. Furthermore, the proposed method can be deployed in modern LTE system with limited cost

Interference mitigation using group decoding in multiantenna systems

fi=vertaisarvioitu|en=peerReviewed

High capacity multiuser multiantenna communication techniques

One of the main issues involved in the development of future wireless communication systems is the multiple access technique used to efficiently share the available spectrum among users. In rich multipath environment, spatial dimension can be exploited to meet the increasing number of users and their demands without consuming extra bandwidth and power. Therefore, it is utilized in the multiple-input multiple-output (MIMO) technology to increase the spectral efficiency significantly. However, multiuser MIMO (MU-MIMO) systems are still challenging to be widely adopted in next generation standards. In this thesis, new techniques are proposed to increase the channel and user capacity and improve the error performance of MU-MIMO over Rayleigh fading channel environment. For realistic system design and performance evaluation, channel correlation is considered as one of the main channel impurities due its severe influence on capacity and reliability. Two simple methods called generalized successive coloring technique (GSCT) and generalized iterative coloring technique (GICT) are proposed for accurate generation of correlated Rayleigh fading channels (CRFC). They are designed to overcome the shortcomings of existing methods by avoiding factorization of desired covariance matrix of the Gaussian samples. The superiority of these techniques is demonstrated by extensive simulations of different practical system scenarios. To mitigate the effects of channel correlations, a novel constellation constrained MU-MIMO (CC-MU-MIMO) scheme is proposed using transmit signal design and maximum likelihood joint detection (MLJD) at the receiver. It is designed to maximize the channel capacity and error performance based on principles of maximizing the minimum Euclidean distance (dmin) of composite received signals. Two signal design methods named as unequal power allocation (UPA) and rotation constellation (RC) are utilized to resolve the detection ambiguity caused by correlation. Extensive analysis and simulations demonstrate the effectiveness of considered scheme compared with conventional MU-MIMO. Furthermore, significant gain in SNR is achieved particularly in moderate to high correlations which have direct impact to maintain high user capacity. A new efficient receive antenna selection (RAS) technique referred to as phase difference based selection (PDBS) is proposed for single and multiuser MIMO systems to maximize the capacity over CRFC. It utilizes the received signal constellation to select the subset of antennas with highest (dmin) constellations due to its direct impact on the capacity and BER performance. A low complexity algorithm is designed by employing the Euclidean norm of channel matrix rows with their corresponding phase differences. Capacity analysis and simulation results show that PDBS outperforms norm based selection (NBS) and near to optimal selection (OS) for all correlation and SNR values. This technique provides fast RAS to capture most of the gains promised by multiantenna systems over different channel conditions. Finally, novel group layered MU-MIMO (GL-MU-MIMO) scheme is introduced to exploit the available spectrum for higher user capacity with affordable complexity. It takes the advantages of spatial difference among users and power control at base station to increase the number of users beyond the available number of RF chains. It is achieved by dividing the users into two groups according to their received power, high power group (HPG) and low power group (LPG). Different configurations of low complexity group layered multiuser detection (GL-MUD) and group power allocation ratio (η) are utilized to provide a valuable tradeoff between complexity and overall system performance. Furthermore, RAS diversity is incorporated by using NBS and a new selection algorithm called HPG-PDBS to increase the channel capacity and enhance the error performance. Extensive analysis and simulations demonstrate the superiority of proposed scheme compared with conventional MU-MIMO. By using appropriate value of (η), it shows higher sum rate capacity and substantial increase in the user capacity up to two-fold at target BER and SNR values

A survey on hybrid beamforming techniques in 5G : architecture and system model perspectives

The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers' structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain