A frequency set adaptive optimization algorithm for differential frequency hopping network based on cognitive radio and Latin squares

Differential frequency hopping (DFH) was believed to be an effective FH technique for increasing data rate of FH communication system. Cognitive radio (CR) users can use the CR technology to sense the surrounding RF environment, search for available spectrum resources and access spectrum dynamically. The cognitive radio technology and applied mathematics are introduced in DFH. And the Latin squares based frequency set adaptive optimization (LS-FSAO) algorithm is proposed. In short, the frequency set is divided into many frequency micro-sets after the spectrum sensing, and the micro-sets are assigned to DFH users with dynamic Latin squares. The users' frequency micro-sets are dissimilar during a same time slot to cut down the Multiple Access Interference (MAI), Partial Band Jamming (PBJ) and Multi-Tone Jamming (MTJ). The scenario simulations of the LS-FSAO based DFH network and the traditional DFH are performed, respectively. The results show that the LS-FSAO DFH can obtain favorable network performance.