Achievement of interference alignment in general underlay cognitive radio networks: Scenario classification and adaptive spectrum sharing

Abstract

Interference alignment (IA) is suitable for cognitive radio networks (CRNs). However, in IA spectrum sharing (SS) process of general underlay CRNs, transmit power of cognitive radio transmitters usually should be reduced to satisfy interference constraint of primary user (PU), which may lead to low signal-to-noise-ratio at cognitive radio receivers (CRRs). Consequently, sum rate of cognitive users (CUs) may fall short of the theoretical maximum through IA. To solve this problem, we propose an adaptive IA SS method for general distributed multi-user multi-antenna CRNs. The relationship between interference and noise power at each CRR is analyzed according to channel state information, interference requirement of PU, and power budget of CUs. Based on the analysis, scenarios of the CRN are classified into 4 cases, and corresponding IA SS algorithms are properly designed. Transmit power adjustment, CU access control and adjusted spatial projection are used to realize IA among CUs. Compared with existing methods, the proposed method is more general because of breaking the restriction that CUs can only transmit on the idle sub-channels. Moreover, in comparison to other five IA SS methods applicable in general CRN, the proposed method leads to improved achievable sum rate of CUs while guarantees transmission of PU.