基于改进二进制人工蜂群算法的多用户检测器

最优多用户检测(OMD)技术可以达到理论上的最小错误概率，但已经证明它是一个非确定多项式(NP)问题。作为一种新型的群智能算法，人工蜂群(ABC)算法已被广泛用于各种优化问题，但传统二进制人工蜂群算法具有收敛速度过慢、易陷入局部最优等缺点。针对这一缺点，提出了一种改进二进制人工蜂群算法并将其用于求解最优多用户检测问题。算法简化了初始化的过程，采用单维求反的邻域搜索策略，计算量与最优多用户检测相比明显降低。仿真结果表明，提出的多用户检测方案在抗多址干扰和抗“远近”效应能力方面与传统检测方案相比，都有显著提高。

Multi-user detector based on improved binary artificial bee colony algorithm

Optimum Multi-user Detection (OMD) technique can achieve the theoretical minimum error probability, but it has been proven to be a Non-deterministic Polynomial (NP) problem. As a new swarm intelligence algorithm, Artificial Bee Colony (ABC) algorithm has been widely used in various optimization problems. However, the traditional Binary Artificial Bee Colony (BABC) algorithm has the shortcomings of slower convergence speed and falling into local optimum easily. Concerning the shortcomings, an improved binary artificial bee colony algorithm was proposed and used for optimum multi-user detection. The initialization process was simplified. The one-dimensional-reversal neighborhood search strategy was adopted. Compared with optimum multi-user detection, the computation complexity of the improved algorithm declines obviously. The simulation results show that the proposed scheme has significant performance improvement over the conventional detection in anti-multiple access interference and near-far resistance.