Interference Alignment in Multi-Input Multi-Output Cognitive Radio-Based Network

Abstract

This study investigates the interference alignment techniques for cognitive radio networks toward 5G to meet the demand and challenges for future wireless communications requirements. In this context, we examine the performance of the interference alignment in two parts. In the first part of this chapter, a multi-input multi-output (MIMO) cognitive radio network in the presence of multiple secondary users (SUs) is investigated. The proposed model assumes that linear interference alignment is used at the primary system to lessen the interference between primary and secondary networks. Herein, we derive the closed-form mathematical equations for the outage probability considering the interference leakage occurred in the primary system. The second part of this study analyzes the performance of interference alignment for underlay cognitive two-way relay networks with channel state information (CSI) quantization error. Here, a two-way amplify-and-forward relaying scheme is considered for independent and identically distributed Rayleigh fading channel. The closed-form average pairwise error probability expressions are derived, and the effect of CSI quantization error is analyzed based on the bit error rate performance. Finally, we evaluate the instantaneous capacity for both primary and secondary networks * .

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.…”

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

“…However, in the proposed scheme shown in Figure 2, we adopt the linear IA method to mitigate the interference occurring at the SN without reducing the powers of the SUs. With the aid of precoding and linear suppression matrices, the single symbol detection at the ith hop (or i + 1th relay) can be expressed as [31]:…”

“…Note that all signal and system model parameters are listed in Table 1. The interference between PN and SN can be perfectly aligned if the following conditions are satisfied [31]:…”