MIMO Interference Alignment Over Correlated Channels with Imperfect CSI

Interference alignment (IA), given uncorrelated channel components and perfect channel state information, obtains the maximum degrees of freedom in an interference channel. Little is known, however, about how the sum rate of IA behaves at finite transmit power, with imperfect channel state information, or antenna correlation. This paper provides an approximate closed-form signal-to-interference-plus-noise-ratio (SINR) expression for IA over multiple-input-multiple-output (MIMO) channels with imperfect channel state information and transmit antenna correlation. Assuming linear processing at the transmitters and zero-forcing receivers, random matrix theory tools are utilized to derive an approximation for the post-processing SINR distribution of each stream for each user. Perfect channel knowledge and i.i.d. channel coefficients constitute special cases. This SINR distribution not only allows easy calculation of useful performance metrics like sum rate and symbol error rate, but also permits a realistic comparison of IA with other transmission techniques. More specifically, IA is compared with spatial multiplexing and beamforming and it is shown that IA may not be optimal for some performance criteria.Comment: 21 pages, 7 figures, submitted to IEEE Transactions on Signal Processin

Position and Orientation Estimation through Millimeter Wave MIMO in 5G Systems

Millimeter wave signals and large antenna arrays are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are well-known, their potential advantages for accurate positioning are largely undiscovered. We derive the Cram\'{e}r-Rao bound (CRB) on position and rotation angle estimation uncertainty from millimeter wave signals from a single transmitter, in the presence of scatterers. We also present a novel two-stage algorithm for position and rotation angle estimation that attains the CRB for average to high signal-to-noise ratio. The algorithm is based on multiple measurement vectors matching pursuit for coarse estimation, followed by a refinement stage based on the space-alternating generalized expectation maximization algorithm. We find that accurate position and rotation angle estimation is possible using signals from a single transmitter, in either line-of- sight, non-line-of-sight, or obstructed-line-of-sight conditions.Comment: The manuscript has been revised, and increased from 27 to 31 pages. Also, Fig.2, Fig. 10 and Table I are adde

Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks

In this correspondence, the comprehensive problem of joint power, rate, and subcarrier allocation have been investigated for enhancing the spectral efficiency of multi-user orthogonal frequency-division multiple access (OFDMA) cognitive radio (CR) networks subject to satisfying total average transmission power and aggregate interference constraints. We propose novel optimal radio resource allocation (RRA) algorithms under different scenarios with deterministic and probabilistic interference violation limits based on a perfect and imperfect availability of cross-link channel state information (CSI). In particular, we propose a probabilistic approach to mitigate the total imposed interference on the primary service under imperfect cross-link CSI. A closed-form mathematical formulation of the cumulative density function (cdf) for the received signal-to-interference-plus-noise ratio (SINR) is formulated to evaluate the resultant average spectral efficiency (ASE). Dual decomposition is utilized to obtain sub-optimal solutions for the non-convex optimization problems. Through simulation results, we investigate the achievable performance and the impact of parameters uncertainty on the overall system performance. Furthermore, we present that the developed RRA algorithms can considerably improve the cognitive performance whilst abide the imposed power constraints. In particular, the performance under imperfect cross-link CSI knowledge for the proposed `probabilistic case' is compared to the conventional scenarios to show the potential gain in employing this scheme