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Dynamic Interference Control in OFDM-Based Cognitive Radio Network Using Genetic Algorithm

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  • Hamza Khan
  • Sang-Jo Yoo

Abstract

In OFDM-based cognitive radio networks, minimizing the interference caused to the primary user (PU) by the substantial amount of out-of-band (OOB) emission is a great challenge. In this paper, we propose a dynamic interference control method using the additive signal side lobe reduction technique and genetic algorithm (GA) in CR-OFDM systems. Additive signal side lobe reduction technique is based on adding a complex array to modulated data symbols in the constellation plane for side lobe reduction in OFDM system. In the proposed method, GA generates optimum additive signal which can effectively reduce the OOB signal interference to the primary system. The GA also strives to keep the interference below a predefined tolerable limit and at the same time it maximizes secondary user's transmission opportunity. The results show that the side lobes of the OFDM-based secondary user signal can be reduced by up to 38 dB and the PU interference tolerable limit can be satisfied at the cost of a minor addition in bit error rate (BER). The results further show that the proposed method delivers better performance as compared to non-GA additive signal method in terms of side lobe reduction as well as BER.

Suggested Citation

  • Hamza Khan & Sang-Jo Yoo, 2015. "Dynamic Interference Control in OFDM-Based Cognitive Radio Network Using Genetic Algorithm," International Journal of Distributed Sensor Networks, , vol. 11(9), pages 870607-8706, September.
    • Handle: RePEc:sae:intdis:v:11:y:2015:i:9:p:870607
    DOI: 10.1155/2015/870607
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