Robust Lattice Alignment for $K$-User MIMO Interference Channels With Imperfect Channel Knowledge

Abstract

Abstract-In this paper, we consider a robust lattice alignment design for K-user quasi-static MIMO interference channels with imperfect channel knowledge. With random Gaussian inputs, the conventional interference alignment (IA) method has the feasibility problem when the channel is quasi-static. On the other hand, structured lattices can create structured interference as opposed to the random interference caused by random Gaussian symbols. The structured interference space can be exploited to transmit the desired signals over the gaps. However, the existing alignment methods on the lattice codes for quasi-static channels either require infinite SNR or symmetric interference channel coefficients. Furthermore, perfect channel state information (CSI) is required for these alignment methods, which is difficult to achieve in practice. In this paper, we propose a robust lattice alignment method for quasi-static MIMO interference channels with imperfect CSI at all SNR regimes, and a two-stage decoding algorithm to decode the desired signal from the structured interference space. We derive the achievable data rate based on the proposed robust lattice alignment method, where the design of the precoders, decorrelators, scaling coefficients and interference quantization coefficients is jointly formulated as a mixed integer and continuous optimization problem. The effect of imperfect CSI is also accommodated in the optimization formulation, and hence the derived solution is robust to imperfect CSI. We also design a low complex iterative optimization algorithm for our robust lattice alignment method by using the existing iterative IA algorithm that was designed for the conventional IA method. Numerical results verify the advantages of the proposed robust lattice alignment method compared with the TDMA, two-stage ML decoding, generalized Han-Kobayashi (HK), distributive IA and conventional IA methods in the literature.

Performance Analysis and Optimization for Interference Alignment Over MIMO Interference Channels With Limited Feedback

“…Hence, the average transmission rate for the th data stream of transmitter-receiver link can be computed as (11) (12) (13) where is the exponential integral function, is a certain feedback bits allocation result related to receiver , and is a combination set on the numbers of data streams fulfilling the feasibility conditions [25], [26]. The proof of the above expression is presented in Appendix I.…”

“…In order to solve this challenging problem, the authors in [12] propose to perform opportunistic IA by making use of channel reciprocity, but it is only applicable to time division duplex (TDD) systems. In [13], a lattice interference alignment is proposed, which only requires partial CSI. Moreover, blind IA without any CSI is realized in some special cases [14].…”

Robust joint signal and interference alignment in cognitive radio networks with ellipsoidal channel state information uncertainties

“…In [6,7], Cadambe-Jafar-based IA schemes have been developed to null interference to the PUs, but requiring perfect channel state information (CSI). The practical CSI is inevitably corrupted by quantisation errors or estimation errors, which may heavily deteriorate the system performance [8][9][10][11]. Recently, the work [11] aimed for robust IA in CR networks where the CSI errors are bounded spherically.…”

TLS-based Interference Alignment Algorithm for Symmetric MIMO Interference Network with CSI Errors

“…In [9], the authors investigate an iterative beamforming design algorithm so as to maximize the sum outage rate for MIMO interference networks. A robust lattice alignment method which is designed by using the existing conventional iterative IA algorithm is presented in [10] for quasi-static MIMO interference networks with imperfect CSI. In addition, [11] and [12] investigate the effect of CSI mismatch and develop several adaptive interference alignment with CSI error.…”