Cognitive Tropospheric Scatter Communication
Chenglong Li, Xihong Chen, Xiaopeng Liu · IEEE Transactions on Vehicular Technology · 2017
Tropospheric scatter as a promising communication for beyond line-of-sight links between remote geographic areas, regains its predominance especially in military applications recently when considering microwave and cable systems are not feasible. In this paper, we propose cognitive troposcatter (short for tropospheric scatter) communication, which aims to improve the quality and capacity of troposcatter communication. Hybrid cognitive troposcatter communication scenarios and cognitive system architecture are established at first. Physical awareness objects including link geometry, nonhomogeneities, and meteorological conditions, are studied and then optimal working frequency has been calculated for specific link scenarios. More importantly, we investigate the potential of applying cognitive radio techniques in troposcatter communication due to the requirement of expanding services and capacity. Focusing on maximal ratio combing (MRC), we derive exact series-form expression of detection probability for diversity reception over Nakagami-m channel. Finally, we evaluate the performance of detection based on MRC techniques over fading channel. Numerical and simulation results demonstrate diversity promotes the detection performance in case of rain, low signal-to-noise ratio, and high antenna elevation.