Performance analysis of spatially distributed MIMO systems

With the growing popularity of ad-hoc sensor networks, spatially distributed multiple-input multiple-output (MIMO) systems have drawn a lot of attention. This work considers a spatially distributed MIMO system with randomly distributed transmit and receive antennas over spatial regions. The authors use the modal decomposition of wave propagation to analyse the performance limits of such system, since the sampling of the spatial regions populated with antennas is a form of mode excitation. Specifically, they decompose signals into orthogonal spatial modes and apply concepts of MIMO communications to quantify the instantaneous capacity and the outage probability. The authors’ analysis shows that analogous to conventional point-to-point MIMO system, the instantaneous capacity of spatially distributed MIMO system over Rayleigh fading channel is equivalent to a Gaussian random variable. Afterwards, they derive an accurate closed-form expression for the outage probability of proposed system utilising the definition of instantaneous capacity. Besides, in rich scattering environment, the spatially distributed MIMO system provides best performance when the spatial regions are of same size, and each region is equipped with equal number of antennas. Furthermore, to facilitate the total transmit power allocation among the channels, they propose an algorithm which indicates a significant performance improvement over conventional equal transmit power allocation scheme, even at low signal-to-noise ratio

Information Theoretic Limits for Wireless Information Transfer Between Finite Spatial Regions

Since the first multiple-input multiple-output (MIMO) experiments performed at Bell Laboratories in the late 1990’s, it was clear that wireless communication systems can achieve improved performances using multiple antennas simultaneously during transmission and reception. Theoretically, the capacity of MIMO systems scales linearly with the number of antennas in favorable propagation conditions. However, the capacity is significantly reduced when the antennas are collocated. A generalized paradigm for MIMO systems, spatially distributed MIMO systems, is proposed as a solution. Spatially distributed MIMO systems transmit information from a spatial region to another with each region occupying a large number of antennas. Hence, for a given constraint on the size of the spatial regions, evaluating the information theoretic performance limits for information transfer between regions has been a central topic of research in wireless communications. This thesis addresses this problem from a theoretical point of view. Our approach is to utilize the modal decomposition of the classical wave equation to represent the spatially distributed MIMO systems. This modal analysis is particularly useful as it advocates a shift of the “large wireless networks” research agenda from seeking “universal” performance limits to seeking a multi-parameter family of performance limits, where the key parameters, space, time and frequency are interrelated. However, traditional performance bounds on spatially distributed MIMO systems fail to depict the interrelation among space, time and frequency. Several outcomes resulting from this thesis are: i) estimation of an upper bound to degrees of freedom of broadband signals observed over finite spatial and temporal windows, ii) derivation of the amount of information that can be captured by a finite spatial region over a finite bandwidth, iii) a new framework to illustrate the relationship between Shannon’s capacity and the spatial channels, iv) a tractable model to determine the information capacity between spatial regions for narrowband transmissions. Hence, our proposed approach provides a generalized theoretical framework to characterize realistic MIMO and spatially distributed MIMO systems at different frequency bands in both narrowband and broadband conditions

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Analysis of cyclic delay diversity on DVB-H systems over spatially correlated channel

The objective of this work is to research and analyze the performance of Cyclic Delay Diversity (CDD) with two transmit antenna on DVB-H systems operating in spatially correlated channel. It is shown in this paper that CDD can achieve desirable transmit diversity gain over uncorrelated channel with or without receiver diversity. However, in reality, the respective signal paths between spatially separated antennas and the mobile receiver is likely to be correlated because of insufficient antenna separation at the transmitter and the lack of scattering effect of the channel. Under this spatially correlated channel, it is apparent that CDD cannot achieve the same diversity gain as obtained under the uncorrelated channel. In this paper, a new upper bound on the pairwise error probability (PEP) of the CDD with spatial correlation of two transmit antennas is derived. The upper bound is used to study the CDD theoretical error performance and diversity gain losses over a generalized spatially correlated Rayleigh channel. This theoretical analysis is validated by the simulation of DVB-H systems with two transmit antennas and the CDD scheme. Both the theoretical and simulated results give the valuable insight that the CDD ability to perform well with a certain amount of channel correlation

On the relation between energy efficiency and spectral efficiency of multiple-antenna systems

Motivated by the increasing interest in energy-efficient communication systems, the relation between energy efficiency (EE) and spectral efficiency (SE) for multiple-input-multiple-output (MIMO) systems is investigated in this paper. To provide insights into the design of practical MIMO systems, we adopt a realistic power model and consider both independent Rayleigh fading and semicorrelated fading channels. We derived a novel and closed-form upper bound (UB) for the system EE as a function of SE. This UB exhibits great accuracy for a wide range of SE values and, thus, can be utilized for explicit assessment of the influence of SE on EE and for analytically addressing the EE optimization problems. Using this tight EE UB, our analysis unfolds two EE optimization issues: Given the number of transmit and receive antennas, an optimum value of SE is derived, such that the overall EE can be maximized, and given a specific value of SE, the optimal number of antennas is derived for maximizing the system EE