Biologically-Inspired Foraging Decision Making in Distributed Cognitive Radio Networks

The dynamic spectrum management techniques have been introduced to address the current Radio Frequency bands inefficiency challenges. Cognitive Radio (CR) technology has been regarded as the most promising technology in the dynamic spectrum management area. One of the major aspects of the spectrum management is the decision making ability of CR users. The dynamic reconfiguration of both the operating frequency and channel bandwidth in a distributed CR network has not received sufficient attention despite their importance in spectrum decision making. Few research works have attempted to address the dynamic reconfiguration of frequency and channel bandwidth problems using various approaches. However, due to certain challenges such as high computational complexity, ambiguity, repeatability and the lack of optimality with the existing approaches, researchers are still trying to explore newer methods that can achieve optimal spectrum management. Hence, this paper presents a biologically-inspired optimal foraging model for dynamic reconfiguration of frequency and channel bandwidth in a distributed cognitive mobile adhoc network. One of the main advantages of biologically-inspired foraging model is its analytical simplicity and optimum solution. The mean efficiency and Distance travelled by SUs before finding available frequency were measured. The two metrics were measured when subjected to different SUs positions and Giving-Up Time. It was generally observed that the SUs perform better when 0 < X_o ≤ 0.2 and GUT ≤ 50 in the achieved mean efficiency and distance travelled to find available frequency.