To further suppress the multiple-access interference (MAI) in frequency-hopping multiple-access (FHMA) system, a novel kind of FH sequence set named as no-hit-zone (NHZ) sequence, is proposed for an FHMA system with M-ary FSK modulation (MFSK/FHMA) in this paper. Expressions for the decision variables are derived for the asynchronous MFSK/FHMA system with NHZ sequence set (MFSK/FHMA-NHZ) under a slow Rayleigh-fading channel model. For the special case of M=2, accurate analytic bit error rate (BER) is derived as a function of maximum relative delay D and the number of users K by a characteristic function method. The theoretical results validated by Monte Carlo simulations are used to investigate the dependence of the average BER on D and K. Comparison with the MFSK/FHMA system with Markov hit pattern (MFSK/FHMA-Markov) shows that MFSK/FHMA-NHZ system performs better than Markov hit pattern system as long as D is restricted in a certain range and further, the gain in the performance increases with increase in the value of K.

There are two major challenges in wide-band spectrum sensing in a heterogenous spectrum environment. One is the spectrum acquisition in the wide-band scenario due to limited sampling capability; the other is how to collaborate in a heterogenous spectrum environment. Compressed spectrum sensing is a promising technology for wide-band signal acquisition but it requires effective collaboration to combat noise. However, most collaboration methods assume that all the secondary users share the same occupancy of primary users, which is invalid in a heterogenous spectrum environment where secondary users at different locations may be affected by different primary users. In this paper, we propose an automatic clustering collaborative compressed spectrum sensing (ACCSS) algorithm. A hierarchy probabilistic model is proposed to represent the compressed reconstruction procedure, and Dirichlet process mixed model is introduced to cluster the compressed measurements. Cluster membership estimation and compressed spectrum reconstruction are jointly implemented in the fusion center. Based on the probabilistic model, the compressed measurements from the same cluster can be effectively fused and used to jointly reconstruct the corresponding primary user's spectrum signal. Consequently, the spectrum occupancy status of each primary user can be attained. Numerical simulation results demonstrate that the proposed ACCSS algorithm can effectively estimate the cluster membership of each secondary user and improve compressed spectrum sensing performance under low signal-to-noise ratio.