Interference Alignment Based on Rank Constraint in MIMO Cognitive Radio Networks

Abstract

Abstract:In this paper, we focus on the interference management in the cognitive radio (CR) network comprised of multiple primary users (PUs) and multiple secondary users (SUs). Firstly, two interference alignment (IA) schemes are proposed to mitigate the interference among PUs. The first one is an interference rank minimization (IRM) scheme, which aims to minimize the rank of the joint interference matrix via alternating between the forward and reverse communication links. Considering the overhead of information exchanged between the transmitters and receivers in the IRM scheme, we further develop an interference subspace distance minimization (ISDM) scheme which runs at the transmitters only. The ISDM scheme focuses on aligning the subspaces spanned by interference with an aligned subspace introduced in this paper. For the secondary network, though IRM and ISDM mitigate the received interference at secondary receivers, they make no attempt to eliminate the interference from SUs to PUs. To address this, we improve the IRM and ISDM schemes by putting a rank constraint into their optimizations, where the rank constraint forces the ranks of the interference matrices from SUs to PUs to be zero. Simulation results validate the effectiveness of the proposed schemes in terms of the average sum rate.

A Novel Codeword Selection Scheme for MIMO-MAC Lower-Bound Maximization

“…Then it finds the location index Limited feedback [ 25 , 26 ]. Because the channel matrix dimension is larger than the precoding matrix, the feedback precoding algorithm is better, and the limited feedback of IA achieves greater performance improvement with less feedback and has been widely studied [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ].…”

“…The limited feedback of IA shares the same codebook between the transmitter and receiver, and the receiver quantizes the channel matrix or precoding according to the obtained CSI and sends feedback for the location index of the quantization codeword [ 3 , 4 ]. Because the quantized channel matrix has a larger dimension than the quantized precoding matrix, the quantized precoding scheme has been widely studied [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. This paper proposes a MIMO Multiple Access Channel (MIMO-MAC) limited feedback IA algorithm that maximizes the rate lower-bound of the system user.…”

PAPR and ISI Reduction in Cognitive Radio Network based 5G Network using Massive MIMO SC - FDMA ES.

“…Interference is the major cause to downgrade performances of network. To mitigate interference in CRN; Interference Subspace Distance Minimization (ISDM) scheme is developed [7]. To define the rank constraint scheme an antenna technology called MIMO is used.…”

Secure cognitive radio‐based synchronized transmission of 5G signals using massive MIMO‐OFDM‐ES

“…In a CRN, interference can degrade the network. The interference subspace distance minimization (ISDM) has been developed to mitigate interference in a CRN . MIMO antenna technologies are used in this system model, which applies a rank constraint scheme.…”

“…The interference subspace distance minimization (ISDM) has been developed to mitigate interference in a CRN. 8 MIMO antenna technologies are used in this system model, which applies a rank constraint scheme. MIMO has been extended to massive MIMO (MaMi) technologies involving hundreds of antennas.…”