Interference Alignment in Multi-Hop Cognitive Radio Networks under Interference Leakage

Abstract

In this work, we examine the interference alignment (IA) performance of a multi-input multi-output (MIMO) multi-hop cognitive radio (CR) network in the presence of multiple primary users. In the proposed architecture, it is assumed that linear IA is adopted at the secondary network to alleviate the interference between primary and secondary networks. By doing so, the secondary source can communicate with the secondary destination via multiple relays without causing any interference to the primary network. Even though linear IA can suppress the interference in CR networks considerably, interference leakages may occur due to a fast fading channel. To this end, we focus on the performance of the secondary network for two different cases: (i) the interference is perfectly aligned; (ii) the impact of interference leakages. For both cases, closed-form expressions of outage probability and ergodic capacity are derived. The results, which are validated by Monte Carlo simulations, show that interference leakages can deteriorate both system performance and the diversity gains considerably.

Interference‐resilient spectrum sharing with collision detection and data recovery for cognitive radio networks

“…Most of these approaches are based on precoding and linear interference suppression matrices so that the interference signal can be confined in a smaller subspace and cancelled by projecting the received signal onto a subspace orthogonal to that of interference. Some results on the application of interference alignment techniques, in CR networks, can be found in the literature 18–22 . These approaches assume prior knowledge about the signaling dimensions and corresponding subspaces of PUs/SUs, the estimation of which is generally difficult in practical scenarios of dynamic channel conditions and concurrent transmission of PUs/SUs.…”

“…Some results on the application of interference alignment techniques, in CR networks, can be found in the literature. [18][19][20][21][22] These approaches assume prior knowledge about the signaling dimensions and corresponding subspaces of PUs/SUs, the estimation of which is generally difficult in practical scenarios of dynamic channel conditions and concurrent transmission of PUs/SUs.…”

Special Issue “Selected Papers from the 2018 41st International Conference on Telecommunications and Signal Processing (TSP)”

“…In the next paper [2], E. Erdogan et al examine the interference alignment (IA) performance of a multi-input multi-output (MIMO) multi-hop cognitive radio (CR) network in the presence of multiple primary users. In the proposed architecture, it is assumed that linear IA is adopted at the secondary network to alleviate the interference between primary and secondary networks.…”