Optimal energy efficient scheme for MIMO-based cognitive radio networks with antenna selection

Multiple-input multiple-output (MIMO), which is also known as large-scale antenna system, is a promising technology for achieving the high spectrum efficiency of wireless communications networks. On the other hand, as a smart spectrum sharing technology, Cognitive Radio Network (CRN) is also expected to improve the utilization of spectrum usage for conciliating the current spectrum demand growth. Thus, the combination of MIMO and CRN has received extensive research attention in recent years. Although the large-scale antenna system can yield large network capacities, the radio-frequency (RF) chain also increases as the number of antennas gets large, which also increases the computational complexity, energy consumption, and hardware cost for the wireless networks. As a novel signal processing technology, antenna selection can reduce the number of RF chains while guaranteeing the performance under the system requirements. However, how to efficiently integrate these techniques to optimize energy efficiency still remains as an open and challenging problem. To overcome these challenges, in this paper we propose the optimal energy efficiency scheme for MIMO-based cognitive radio networks with antenna selection. In particular, we develop the joint transmit-power allocation and antenna subsets selection schemes for the transmitter to maximize the CRN's energy efficiency implemented under the constrains of the maximum interference caused by the secondary users (SU) to the primary users (PU), maximum transmission power from SU, and the minimum transmission rate in SU link. Finally, the obtained simulation results validate and evaluate our proposed schemes.