基于膜量子布谷鸟搜索的双通道网络频谱资源分配

无线双通道Ad Hoc网络中, 有效分配簇间码分频谱资源是提高资源利用效率的关键技术之一.综合考虑子簇码分频谱资源需求和分配公平性, 给出了簇间码分频谱资源分配数学模型, 并转换为以最大化码分频谱资源效益和分配公平性为多目标的受约束离散优化问题.结合膜结构、量子计算和布谷鸟搜索算法, 提出一种新的离散组合优化算法——膜量子布谷鸟搜索算法.该算法使用量子鸟窝表征问题潜在解, 利用布谷鸟寻窝产卵的演化方法在基础膜中寻求单目标最优解, 通过膜间信息共享和非支配解等级排序求出具有多目标最优解的表层膜Pareto前端解集.仿真结果证明, 与经典优化算法相比, 该算法不仅能够同时求解单目标和多目标最优解, 而且具有更优的收敛性能, 能更好地实现码分频谱资源效益最优化.

Frequency spectrum resource allocation based on membrane-inspired quantum cuckoo search for wireless dual-channel ad hoc network

In wireless dual-channel ad hoc network, allocating the inter-cluster code resource efficiently is the key to improve the code frequency resource utilization efficiency. Taken the code spectrum resource requirement and assignment fairness for each cluster into account, a mathematical model of inter-cluster code frequency spectrum resource allocation is proposed, and converted into a constrained discrete multi-objective optimization problem. In addition, a novel discrete combinator optimization algorithm called membrane-inspired quantum cuckoo search algorithm (MQCSA) is presented based on membrane structure, quantum computation and cuckoo search algorithm(CSA). In MQCSA, quantum nest is used to represent the potential solutions, and the global optimal solution of single objective in the elementary membranes is searched with CSA, and then the optimal Pareto front solutions are calculated for obtaining multi-objective optimal solutions from the skin membrane according to inter-membrane searched information sharing and non-dominated solutions sorting. Finally, a novel code resource allocation method based on MQCSA is designed. The results show that, both the optimal solutions for single-objective and multiple-objective optimization problems can be solved, and higher efficiency on convergence performance can be obtained, which leads to the maximization of code frequency spectrum resource.