基于干扰子空间估计的跳频多址信号检测

通过对跳频多址信号的时频图案分析,建立了基于信号子空间的系统模型和跳频多址信号的解相关检测算法.该算法采用子空间跟踪的思想,将干扰子空间从检测信号空间上予以消除,克服了传统检测器需要知道系统中所有用户跳频图案的约束和串行干扰消除中的干扰扩散问题.与传统检测器相比,该算法具有更好的系统误码性能、较低的计算复杂度和很好的系统稳健性.MonteCarlo仿真结果表明,在同一个误码率条件下,基于子空间的盲多用户检测器比传统检测器的信噪比提高了2～4dB.

Multi-Access Signal Detection for Frequency Hopping Based on Interference Subspace Estimation

A new blind multiuser detector based on signal subspace estimation was proposed in order to realize multiuser detection for frequency hopping multiple access (FHMA) systems. On the basis of analyzing of time-frequency pattern for FHMA signal, the FHMA system model and decorrelating detection algorithm based on signal subspace were established. Using of idea of subspace tracing, this algorithm can eliminate the interference user signal from the received signal subspace, overcome the restriction that should know all user's frequency hopping patterns and the interference spreading problem in the serial interference cancellation process. Compared to conventional detectors, the proposed subspace-based blind adaptive detector offers better bit error rate (BER) performance, lower computational complexity, and robustness against system user variation. The Monte Carlo simulation results indicate that the signal noise ratio of the proposed blind multiuser detector can be 2-4 dB more than that of conventional detector at the same BER.