For joint sensing of multiple Cognitive Users (CUs), considering the case of fading channels between the CU and the decision center, a joint spectrum sensing algorithm based on Multiple-Access Channels (MAC) was proposed. On the basis of the system structure and signal modeling, the asymptotic behavior and outage probability of the traditional MAC algorithm were analyzed. Under the constraint of the average transmit power of the CU, the transmit gain of the MAC algorithm was optimized to maximize the detection probability; and the problem of minimizing the number of CUs was also studied in the case of certain Quality of Service (QoS). Simulation results show that the proposed MAC algorithm can ensure good detection performance; in particular, it achieves exponential performance improvement in detection error probability.

The adaptability of light source array simplification in channel modeling of wireless optical access network was evaluated, the applicable performance of this simplification to channel characterization under different transmitter configuration, different Field Of View (FOV) and different source radiation pattern was discussed. Simulation results illustrate that the applicable performance has a strong dependence on the FOV, only when the FOV is no less than 60°, the induced deviation to optical path loss and root mean square delay spread are limited within 1.53 dBo and 0.77 ns, respectively.

Concerning the problem of detecting unknown Linear Frequency Modulated (LFM) signal, according to the feature that the phase of the signal is stable, a LFM signal detection method based on the frequency domain phase variance weighting was proposed. The proposed method utilized the characteristics that the phase of LFM signal frequency unit was stable, and the phase of noise frequency unit was random, to weight each frequency unit by the phase variance, which could further restrain the background noise energy disturbances, enhanced the Signal-to-Noise Ratio (SNR) gain of signal detection, and achieved detecting unknown LFM signal. Under simulation conditions, when the input average Spectrum Level Ratio (SLR) was greater than -10 dB, compared with phase difference alignment method, the output average SLR of the proposed method was further improved, and with the input the average SLR became higher, the output SLR was further improved. The theoretical analysis and experimental results show that the proposed method can well enhance the energy of LFM signal, restrain the background noise energy, and improve SNR.