A multi-band wireless local area network (WLAN) enables flexible use of multiple frequency bands. To efficiently monitor radio resources in multi-band WLANs, a distributed-sensing system that employs a number of stations (STAs) is considered to alleviate sensing constraints at access points (APs). This paper examines the distributed sensing that expands the sensing coverage area and monitors multiple object channels by employing STA-based sensing. To avoid issuing unnecessary reports, each STA autonomously judges whether it should make a report by comparing the importance of its own sensing result and that of the overheard report. We address how to efficiently collect the necessary sensing information from a large number of STAs. We propose a reactive reporting scheme that is highly scalable by the number of STAs to collect such sensing results as the channel occupancy ratio. Evaluation results show that the proposed scheme keeps the number of reports low even if the number of STAs increases. Our proposed sensing scheme provides large sensing coverage.

This paper presents the efficiency of a sensing database and caching (SDB) for cognitive radio systems. The proposed SDB stores regulatory information from regulatory databases, and contains sensing information by distributed sensing schemes. Preliminary information processing for instance indexing, sorting, or applying some models or algorithms, etc. can be performed for the stored data. Available information and the results of the information processing are provided to cognitive radios in order to determine available spectrum and to facilitate dynamic spectrum access at lower sensing cost but higher sensing quality. The SDB is implemented in local networks, therefore information exchange between SDB and the cognitive radios can be realized at low latency and the amount of signaling traffic to global network can be reduced. This paper analyzes the effect of SDB and the performance evaluation was done in a certain condition. As a result, by deploying SDB a system can achieve up to 20% of reduction of sensing activities and maximum 1.3 times higher sensing quality.

Due to the advancement of software radio and RF technology, cognitive radio(CR) has become an enabling technology to realize dynamic spectrum access through its spectrum sensing and reconfiguration capability. Robust and reliable spectrum sensing is a key factor to discover spectrum opportunity. Single cognitive radios often fail to provide such reliable information because of their inherent sensitivity limitation. Primary signals that are subject to detection by cognitive radios may become weak due to several factors such as fading and shadowing. One approach to overcome this problem is to perform spectrum sensing by using multiple CRs or multiple spectrum sensors. This approach is known as distributed sensing because sensing is carried out through cooperation of spatially distributed sensors. In distributed sensing, sensors should perform spectrum sensing and forward the result to a destination where data fusion is carried out. Depending on the channel conditions between sensors (sensor-to-sensor channel) and between the sensor and the radio (user-channel), we explore different spectrum sensing algorithms where sensors provide the sensing information either cooperatively or independently. Moreover we investigate sensing schemes based on soft information combining (SC), hard information combining (HC). Finally we propose a two-stage detection scheme that uses both SC and HC. The newly proposed detection scheme is shown to provide improved performance compared to sensing based on either HC or SC alone. Computer simulation results are provided to illustrate the performances of the different sensing algorithms.