Linear Interference Alignment in Full-Duplex MIMO Networks With Imperfect CSI

Abstract

In this paper we consider a system where full-duplex (FD) base-stations (BSs) communicate with half-duplex (HD) downlink (DL) and uplink (UL) users in a multiuser multi-cell network, where all nodes are equipped with multiple antennas. The introduction of FD BSs offers potential to increase spectral efficiency, however it also causes a surge in the number of interference links compared to the HD network counterpart. Here, we apply linear interference alignment (IA) to manage interference in this network under imperfect channel state information (CSI). Firstly, we characterize the performance losses incurred with respect to the achievable sum rate and degrees of freedom (DoF). Results show that the general trend in performance loss is mainly determined by how the error scales with the signal-to-noise ratio (SNR). In particular, full UL and DL DoF can be achieved even under imperfect CSI when the channel error is at least inversely proportional to SNR. Moreover, in such cases the sum rate loss is always finite, and either goes to zero or is upper bounded by a derived value. Secondly, we design two linear IA algorithms applicable to the system under consideration. These are based on minimizing the mean square error (MMSE) and maximizing the signal-to-interference-plus-noise ratio (Max-SINR), and take into account statistical knowledge of the CSI error for added robustness. The proposed algorithms follow specific design principles that distribute the different interference components amongst the various beamformers and result in unitary receivers and precoders. Additionally, we show that under certain conditions both designs result in identical beamforming solutions, even though the MMSE algorithm has lower computational complexity. Thirdly, we also derive the proper condition for IA feasibility in the multi-cell system under consideration.

Multi-objective Antenna Selection in a Full Duplex Base Station

“…The exponential weighted criterion method has a similar parameter w and this parameter is adjusted to its proper value by trial and error. However, in weighted sum method, w can be set by (13). The performance of two solutions are nearly the same.…”

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

“…Applications [56][57][58][59][60] Cognitive Radio Networks [30,41,47,61] K User Interference Channel [27,30,31,46,47] K User M × N MIMO Interference Channels [62,63] 5G Cellular Wireless Networks [64][65][66] Cooperative Interference Networks [66,67] Multihop Interference Networks [68,69] Ad hoc Networks [70,71] Physical Layer Security [72,73] Satellite Networks [74,75] D2D Networks [50,76] IoT Networks [34,35,38,51] Heterogeneous Networks…”

Optimized Time Splitting to Maximize the Lower Bound of Rate with Channel Estimation in An Interference Alignment Based Network

“…Substituting (10) into (7) and with some simple calculations, we can formulate the lower bound of achievable rate for the k-th user pair as…”

“…Substituting (15) into (7) and with some simple calculations, we can get the lower bound of achievable rate for the k-th user pair R L k (α) with RMMSE CE which has the same form as (11). However, the values of A, B, C and D are different from (12) and can be computed as…”

“…With the imperfect CSI, the IA performance is deteriorating sharply and even not better than traditional orthogonal methods [5]. Then, the robust design and performance evaluation of IA with imperfect CSI have been widely studied in [6][7][8][9][10]. For example, a novel IA scheme with imperfect CSI based on antenna selection was proposed to improve the received signal to interference plus noise ratio (SINR) in [6].…”