Tharmalingam Ratnarajah

Bio: Tharmalingam Ratnarajah is an academic researcher from University of Edinburgh. The author has contributed to research in topics: MIMO & Channel state information. The author has an hindex of 42, co-authored 374 publications receiving 5747 citations. Previous affiliations of Tharmalingam Ratnarajah include Ottawa University & Nortel.

A Minorization-Maximization Method for Optimizing Sum Rate in the Downlink of Non-Orthogonal Multiple Access Systems

Abstract: Non-orthogonal multiple access (NOMA) systems have the potential to deliver higher system throughput, compared with contemporary orthogonal multiple access techniques. For a linearly precoded multiple-input single-output (MISO) system, we study the downlink sum rate maximization problem, when the NOMA principle is applied. Being a non-convex and intractable optimization problem, we resort to approximate it with a minorization-maximization algorithm (MMA), which is a widely used tool in statistics. In each step of the MMA, we solve a second-order cone program, such that the feasibility set in each step contains that of the previous one, and is always guaranteed to be a subset of the feasibility set of the original problem. It should be noted that the algorithm takes a few iterations to converge. Furthermore, we study the conditions under which the achievable rates maximization can be further simplified to a low complexity design problem, and we compute the probability of occurrence of this event. Numerical examples are conducted to show a comparison of the proposed approach against conventional multiple access systems.

Large-Scale MIMO Transmitters in Fixed Physical Spaces: The Effect of Transmit Correlation and Mutual Coupling

Abstract: We explore the performance of multiple input multiple output (MIMO) transmitters in correlated channels where increasing numbers of antenna elements are fitted in a fixed physical space. As well investigated in the literature, two main effects emerge in such a design: transmit spatial correlation and mutual antenna coupling. In contrast to the literature however, here we investigate the combined effect of reducing the distance between the antenna elements with increasing the number of elements in a fixed transmitter space. In other words, towards the implementation of large-scale MIMO transmitters in limited physical spaces, we investigate the joint effect of two contradicting phenomena: the reduction of spatial diversity due to reducing the separation between antennas and the increase in transmit diversity by increasing the number of elements. Within this context, we analytically approximate the performance of two distinct linear precoding designs. The theoretical analysis and simulations show the somewhat surprising result that for a given number of receivers the improved transmit diversity dominates the performance of practical linear precoders. Consequently, important benefits in the system sum rate can be gleaned by fitting more antenna elements in a fixed space by employing separations smaller than the wavelength of the transmit frequency.

MIMO Radar and Cellular Coexistence: A Power-Efficient Approach Enabled by Interference Exploitation

Abstract: We propose a novel approach to enable the coexistence between Multi-Input-Multi-Output (MIMO) radar and downlink multiuser multi-input single-output communication system. By exploiting the constructive multiuser interference (MUI), the proposed approach tradeoff useful MUI power for reducing the transmit power, to obtain a power efficient transmission. This paper focuses on two optimization problems: a) Transmit power minimization at the base station (BS), while guaranteeing the receive signal-to-interference-plus-noise ratio (SINR) level of downlink users and the interference-to-noise ratio level to radar; b) Minimization of the interference from BS to radar for a given requirement of downlink SINR and transmit power budget. To reduce the computational overhead of the proposed scheme in practice, an algorithm based on gradient projection is designed to solve the power minimization problem. In addition, we investigate the tradeoff between the performance of radar and communication, and analytically derive the key metrics for MIMO radar in the presence of the interference from the BS. Finally, a robust power minimization problem is formulated to ensure the effectiveness of the proposed method in the case of imperfect channel state information. Numerical results show that the proposed method achieves a significant power saving compared to conventional approaches, while obtaining a favorable performance-complexity tradeoff.

On the Performance of Eigenvalue-Based Cooperative Spectrum Sensing for Cognitive Radio

Abstract: In this paper, the distribution of the ratio of extreme eigenvalues of a complex Wishart matrix is studied in order to calculate the exact decision threshold as a function of the desired probability of false alarm for the maximum-minimum eigenvalue (MME) detector. In contrast to the asymptotic analysis reported in the literature, we consider a finite number of cooperative receivers and a finite number of samples and derive the exact decision threshold for the probability of false alarm. The proposed exact formulation is further reduced to the case of two receiver-based cooperative spectrum sensing. In addition, an approximate closed-form formula of the exact threshold is derived in terms of a desired probability of false alarm for a special case having equal number of receive antennas and signal samples. Finally, the derived analytical exact decision thresholds are verified with Monte-Carlo simulations. We show that the probability of detection performance using the proposed exact decision thresholds achieves significant performance gains compared to the performance of the asymptotic decision threshold.

Sum Rate Analysis of ZF Receivers in Distributed MIMO Systems

Abstract: The performance of single-cell distributed multiple-input multiple-output (D-MIMO) systems is not only affected by small-scale Rayleigh fading but also from large-scale fading and path-loss. In this paper, we elaborate on the sum rate of D-MIMO systems employing linear zero-forcing receivers, accounting for both large and small-scale fading effects, as well as spatial correlation at the transmit side. In particular, we consider the classical lognormal model and propose closed-form upper and lower bounds on the achievable sum rate. Using these bounds as a starting point, we pursue a "large-system" analysis and provide asymptotic expressions when the number of antennas at the base station (BS) grow large, and when the number of antennas at both ends grow large with a fixed and finite ratio. A detailed characterization in the asymptotically high and low signal to noise ratio regimes is also provided. An interesting observation from our results is that in order to maximize the sum rate, the RPs should be placed at unequal distances to the BS when they experience the same level of shadowing. The resulting closed-form expressions are compared with the corresponding results on MIMO optimal receivers.

Table Of Integrals Series And Products

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Random Matrix Theory and Wireless Communications

Abstract: Random matrix theory has found many applications in physics, statistics and engineering since its inception. Although early developments were motivated by practical experimental problems, random matrices are now used in fields as diverse as Riemann hypothesis, stochastic differential equations, condensed matter physics, statistical physics, chaotic systems, numerical linear algebra, neural networks, multivariate statistics, information theory, signal processing and small-world networks. This article provides a tutorial on random matrices which provides an overview of the theory and brings together in one source the most significant results recently obtained. Furthermore, the application of random matrix theory to the fundamental limits of wireless communication channels is described in depth.

An Overview of Massive MIMO: Benefits and Challenges

Abstract: Massive multiple-input multiple-output (MIMO) wireless communications refers to the idea equipping cellular base stations (BSs) with a very large number of antennas, and has been shown to potentially allow for orders of magnitude improvement in spectral and energy efficiency using relatively simple (linear) processing. In this paper, we present a comprehensive overview of state-of-the-art research on the topic, which has recently attracted considerable attention. We begin with an information theoretic analysis to illustrate the conjectured advantages of massive MIMO, and then we address implementation issues related to channel estimation, detection and precoding schemes. We particularly focus on the potential impact of pilot contamination caused by the use of non-orthogonal pilot sequences by users in adjacent cells. We also analyze the energy efficiency achieved by massive MIMO systems, and demonstrate how the degrees of freedom provided by massive MIMO systems enable efficient single-carrier transmission. Finally, the challenges and opportunities associated with implementing massive MIMO in future wireless communications systems are discussed.

5G : A tutorial overview of standards, trials, challenges, deployment, and practice

Abstract: There is considerable pressure to define the key requirements of 5G, develop 5G standards, and perform technology trials as quickly as possible. Normally, these activities are best done in series but there is a desire to complete these tasks in parallel so that commercial deployments of 5G can begin by 2020. 5G will not be an incremental improvement over its predecessors; it aims to be a revolutionary leap forward in terms of data rates, latency, massive connectivity, network reliability, and energy efficiency. These capabilities are targeted at realizing high-speed connectivity, the Internet of Things, augmented virtual reality, the tactile internet, and so on. The requirements of 5G are expected to be met by new spectrum in the microwave bands (3.3-4.2 GHz), and utilizing large bandwidths available in mm-wave bands, increasing spatial degrees of freedom via large antenna arrays and 3-D MIMO, network densification, and new waveforms that provide scalability and flexibility to meet the varying demands of 5G services. Unlike the one size fits all 4G core networks, the 5G core network must be flexible and adaptable and is expected to simultaneously provide optimized support for the diverse 5G use case categories. In this paper, we provide an overview of 5G research, standardization trials, and deployment challenges. Due to the enormous scope of 5G systems, it is necessary to provide some direction in a tutorial article, and in this overview, the focus is largely user centric, rather than device centric. In addition to surveying the state of play in the area, we identify leading technologies, evaluating their strengths and weaknesses, and outline the key challenges ahead, with research test beds delivering promising performance but pre-commercial trials lagging behind the desired 5G targets.