Achievable Energy Efficiency and Spectral Efficiency of Large‐ Scale Distributed Antenna Systems

In the large‐scale distributed antenna system (LS‐DAS), a large number of antenna elements are densely deployed in a distributed way over the coverage area, and all the signals are gathered at the cloud processor (CP) via dedicated fiber links for globally joint processing. Intuitively, the LS‐DAS can inherit the advantage of both large‐scale multiple‐input‐multiple‐output (MIMO) and network densification; thus, it offers enormous gains in terms of both energy efficiency (EE) and spectral efficiency (SE). However, as the number of distributed antenna elements (DAEs) increases, the overhead for acquiring the channel state information (CSI) will increase accordingly. Without perfect CSI at the CP, which is the majority situation in practical applications due to limited overhead, the claimed gain of LS‐DAS cannot be achieved. To solve this problem, this chapter considers a more practical case with only the long‐term CSI including the path loss and shadowing known at the CP. As the long‐term channel fading usually varies much more slowly than the short‐term part, the system overhead can be easily controlled under this framework. Then, the EE‐oriented and SE‐oriented power allocation problems are formulated and solved by fractional programming (FP) and geometric programming (GP) theories, respectively. It is observed that the performance gain with only long‐term CSI is still noticeable and, more importantly, it can be achieved with a practical system cost

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