Interference Alignment and Fairness Algorithms for MIMO Cognitive Radio Systems

Abstract

Interference alignment (IA) is an effective technique to eliminate the interference among wireless nodes. In a multiinput multi-output (MIMO) cognitive radio system, multiple secondary users can coexist with the primary user without generating any interference by using the IA technology. However, few works have considered the fairness of secondary users. In this paper, not only is the interference eliminated by IA, but also the fairness of secondary users is considered by two kinds of algorithms. Without losing generality, one primary user andKsecondary users are considered in the network. Assuming perfect channel knowledge at the primary user, the interference from secondary users to the primary user is aligned into the unused spatial dimension which is obtained by water-filling among primary user. Also, the interference between secondary users can be eliminated by a modified maximum signal-to-interference-plus-noise algorithm using channel reciprocity. In addition, two kinds of fairness algorithms, max-min fairness and proportional fairness, among secondary users are proposed. Simulation results show the effectiveness of the proposed algorithms in terms of suppressed interference and fairness of secondary nodes. What is more, the performances of the two fairness algorithms are compared.

Joint IA and SFBC Macrocells and Small-Cells Coexistence under Minor Information Exchange

“…In order to cancel the interference coming from MBS towards the SUT , we need to compute an appropriate filter matrix at the SUT . From (11) it follows that to satisfy the zerointerference condition the IA-filter matrix at SUT is…”

“…One recent and effective solution to deal with interference in two-tiered networks is the interference alignment (IA) technique. IA has emerged as an essential approach in order to achieve the degrees of freedom (DoF) in interference channels [9][10][11]. In [12] the authors proposed a new IA scheme for the heterogeneous networks with multiple antennas where this scheme successively creates transmit beamforming vectors for the small-cell BSs and for the macro BS assuming that they have different number of transmit antennas.…”