Multiple Antenna Selection for Underlay Cognitive Radio Systems with Interference Constraint

The spectrum sharing concept of Cognitive Radio Networks (CRN) improves the efficiency of spectrum utilization by satisfying the current spectrum demands. The combination of Multiple Input Multiple Output (MIMO) and CRN results in achieving high spectrum efficiency and allocation of more spatial dim...

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Bibliographic Details
Published in:Wireless personal communications 2018, Vol.98 (1), p.1505-1520
Main Authors: Reba, P., Uma Maheswari, Govindaswamy, Satheesh Babu, Moses
Format: Article
Language:English
Subjects:
Antennas
Chains
Codes
Cognitive radio
Communications Engineering
Computer Communication Networks
Computer simulation
Engineering
Interference
MIMO (control systems)
Multiplexing
Networks
Signal,Image and Speech Processing
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Summary:The spectrum sharing concept of Cognitive Radio Networks (CRN) improves the efficiency of spectrum utilization by satisfying the current spectrum demands. The combination of Multiple Input Multiple Output (MIMO) and CRN results in achieving high spectrum efficiency and allocation of more spatial dimensions for SUs. But the main drawback is, as the number of antennas increase, the RF chain also increases thereby increasing the computational complexity and hardware costs. Antenna selection (AS) techniques reduce the number of RF chains while guaranteeing the performance of multiple antenna systems. In this paper, we present an AS scheme; in particular we present a joint transmit and receive multiple AS method for underlay CR environment, thus maintaining the multiplexing benefit of MIMO systems. This technique maximizes the capacity as well as minimizes the symbol error probability while satisfying interference constraint at the primary user receiver. The closed form expression for CDF of SNR of the selected Single Input Single output link is derived. The simulation results show that the proposed method achieves improved performance in terms of SNR.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-017-4931-7