Precoder design for space-time coded systems over correlated Rayleigh fading channels using convex optimization

A class of computationally efficient linear precoders for space-time block coded multiple-input multiple-output wireless systems is derived based on the minimization of the exact symbol error rate (SER) and its upper bound. Both correlations at the transmitter and receiver are assumed to be present, and only statistical channel state information in the form of the transmit and receive correlation matrices is assumed to be available at the transmitter. The convexity of the design based on SER minimization is established and exploited. The advantage of the developed technique is its low complexity. We also find various relationships of the proposed designs to the existing precoding techniques, and derive very simple closed-form precoders for special cases such as two or three receive antennas and constant receive correlation. The numerical simulations illustrate the excellent SER performance of the proposed precoders

CMI analysis and precoding designs for correlated multi-hop MIMO channels

Conditional mutual information (CMI) analysis and precoding design for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels are presented in this paper. Although some particular scenarios have been examined in existing publications, this paper investigates a generally correlated transmission system having spatially correlated channel, mutually correlated source symbols, and additive colored Gaussian noise (ACGN). First, without precoding techniques, we derive the optimized source symbol covariances upon mutual information maximization. Secondly, we apply a precoding technique and then design the precoder in two cases: maximizing the mutual information and minimizing the detection error. Since the optimal design for the end-to-end system cannot be analytically obtained in closed form due to the non-monotonic nature, we relax the optimization problem and attain sub-optimal designs in closed form. Simulation results show that without precoding, the average mutual information obtained by the asymptotic design is very close to the one obtained by the optimal design, while saving a huge computational complexity. When having the proposed precoding matrices, the end-to-end mutual information significantly increases while it does not require resources of the system such as transmission power or bandwidth

High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16x16 and 32x32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.Comment: v3: Performance/complexity comparison of the proposed scheme with other large-MIMO architectures/detectors has been added (Sec. IV-D). The paper has been accepted for publication in IEEE Journal of Selected Topics in Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO Systems. v2: Section V on Channel Estimation is update

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