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Coverage optimization is a big challenge for wireless local area network (WLAN) deployment. The most common problems in coverage are coverage hole and interference. Traditional approaches exploit knowledge of the propagation environment to obtain static network planning and optimization, thus are not adaptable to the changes of environment and network topology. In this paper, a coverage self-optimization solution is proposed for WLAN, which adjusts the power of each beam of access points based on sensor measurement, and the Received Signal Strength (RSS) and Signal-to-Interference ratio (SIR) targets of the sensors to self-optimize coverage performance. Simulation shows that by implementing the proposed solution, coverage problems can be identified and solved adaptively.

-In a spectrum overlay system, the secondary users (SUs) with cognitive radio capability need to detect the presence of primary users promptly and reliably in order to prevent excessive interference. Likewise, to make full use of the available spectra, such systems have to attain low false alarm probability. Having a high detection probability while maintaining a low false alarm probability is challenging as these are conflicting goals; therefore, an appropriate tradeoff needs to be determined. In this paper we propose a "Hierarchical and Adaptive Spectrum Sensing (HASS)" solution to multi-hop cellular networks, which is based on cooperative sensing and soften hard detection fusion mechanisms with one-bit overhead. SUs that are able to make local detection decisions either directly report their one-bit decisions to the cognitive radio base station or they relay their decisions to other favorable SUs based on the states of their reporting channels. If SUs can not make detection decisions, they relay the observed signals to other favorable SUs for further processing. Simulation results show HASS solution improves spectrum sensing performance in multi-hop cellular networks.