Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity

We investigate asymptotic capacity limits of the Gaussian MIMO broadcast channel (BC) with spatially correlated fading to understand when and how much transmit correlation helps the capacity. By imposing a structure on channel covariances (equivalently, transmit correlations at the transmitter side) of users, also referred to as \emph{transmit correlation diversity}, the impact of transmit correlation on the power gain of MIMO BCs is characterized in several regimes of system parameters, with a particular interest in the large-scale array (or massive MIMO) regime. Taking the cost for downlink training into account, we provide asymptotic capacity bounds of multiuser MIMO downlink systems to see how transmit correlation diversity affects the system multiplexing gain. We make use of the notion of joint spatial division and multiplexing (JSDM) to derive the capacity bounds. It is advocated in this paper that transmit correlation diversity may be of use to significantly increase multiplexing gain as well as power gain in multiuser MIMO systems. In particular, the new type of diversity in wireless communications is shown to improve the system multiplexing gain up to by a factor of the number of degrees of such diversity. Finally, performance limits of conventional large-scale MIMO systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure

Blind Estimation of Effective Downlink Channel Gains in Massive MIMO

We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a blind channel estimation method which can be applied at the users and which does not require any downlink pilots. We show that our proposed scheme can substantially outperform the case where each user has only statistical channel knowledge, and that the difference in performance is particularly large in certain types of channel, most notably keyhole channels. Compared to schemes that rely on downlink pilots, our proposed scheme yields more accurate channel estimates for a wide range of signal-to-noise ratios and avoid spending time-frequency resources on pilots.Comment: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 201

Millimetre-wave antennas and systems for the future 5G

Editorial of the special issue on Millimetre-Wave Antennas and Systems for the Future 5

Evaluation of Eigenvalue and Block Diagonalization Beamforming Precoding Performance for 5G Technology over Rician Channel

In traditional wireless cellular, at the same cell, users can cause co-channel interference (CCI) between each other; CCI can deteriorate the channel’s capacity. A multiple-input multiple-output (MIMO) system with beamforming technology solves this CCI problem. Exploiting the channel state information (CSI) in a multi-user MIMO (MU-MIMO) system can improve the performance of the channel link by designing the precoding vectors for every user. A linear precoder has multiple methods, like Block diagonalization precoding (BDP) and Eigenvalue precoding (EP) that facilitate its use. This paper evaluates the symbol-detection performance for BDP and EP in MU-MIMO beamforming over a Rayleigh fading channel. Then, the channel matrix replaces the typical channel assumption with its correlated realistic Rician fading channel. Simulation results show that the Rician fading channel has performance improvement until with low Rician factor value, compared to a conventional channel. The high value of the Rician factor can reduce the error rate

Asymptotic Analysis of Double-Scattering Channels

We consider a multiple-input multiple-output (MIMO) multiple access channel (MAC), where the channel between each transmitter and the receiver is modeled by the doubly-scattering channel model. Based on novel techniques from random matrix theory, we derive deterministic approximations of the mutual information, the signal-to-noise-plus-interference-ratio (SINR) at the output of the minimum-mean-square-error (MMSE) detector and the sum-rate with MMSE detection which are almost surely tight in the large system limit. Moreover, we derive the asymptotically optimal transmit covariance matrices. Our simulation results show that the asymptotic analysis provides very close approximations for realistic system dimensions.Comment: 5 pages, 2 figures, submitted to the Annual Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 201