We have developed the effective algorithm for detecting digital binary phase-shift keyed signals. This algorithm requires a small number of arithmetic operations over the signal period. It can be relat ively easy implemented based on the modern programmable logic devices. It also provides high Interference Immunity by identifying signal presence when signal-to-noise ratio is much less that its working value in the receiving path. The introduced detector has int rinsic frequency selectivity and allows us to form the est imate of the noise level to realize the adaptive determination of decision threshold. In order to get confirmation of the detector operability and performance, we suggest the expressions for false alarm and missing probabilities. In addit ion, we have examine, both theoretically and experimentally, the influence of the detector parameters on its characterist ics.

Background and Objectives: To achieve significant throughput, Interference alignment (IA) is an encouraging technique for wireless Interference networks. In this study, we design an aligned beamformer based on the Interference leakage minimization (ILM) method to reduce the Interference power for a multiple-input multiple-output Interference channel (MIMO-IC). Methods: To deal with the non-convexity of ILM problem, we used a non-convex programming method (i. e., difference of convex [DC]). In this way, the Interference leakage function is reformulated to a DC function including difference of two convex terms. Then, an additive function is defined that includes the DC objective function and a penalty function. Results: We propose a novel DC-based IA algorithm that uses solutions of an upper bound of the additive function in each iteration; as the initial state for the next iteration. Through an iterative manner and for the large values of the penalty factor, the solutions of upper bound function converge to the solutions of the original DC objective function (i. e., Interference leakage function). Conclusion: In contrast to the frequent IA methods, the proposed DC-based IA algorithm updates transmit-and receive-beamformers in each iteration jointly (not alternately). Simulation results indicate that the proposed method outperforms some competitive IA algorithms by providing more throughputs and less Interference leakage.