Cognitive radio (CR) and mobile networks have been a hot topic for extensive study in recent years. Since the spectrum allocation and access are both dynamic, new challenges are introduced into the spectrum management and the applications. In this thesis, for the spectrum assignment problem, we proposed aggregation-aware spectrum assignment (AASA), a spectrum assignment algorithm in cognitive ad-hoc networks. AASA utilizes the small spectrum fragments that cannot be utilized by contiguous spectrum assignment algorithms. To obtain quantitative understanding of current spectrum utilization, we carried out a set of spectrum measurements in the 20MHz to 3GHz spectrum band at 4 locations concurrently in Guangdong province of China, and using these data sets we conducted a set of detailed ana...[ Read more ]

Cognitive radio (CR) and mobile networks have been a hot topic for extensive study in recent years. Since the spectrum allocation and access are both dynamic, new challenges are introduced into the spectrum management and the applications. In this thesis, for the spectrum assignment problem, we proposed aggregation-aware spectrum assignment (AASA), a spectrum assignment algorithm in cognitive ad-hoc networks. AASA utilizes the small spectrum fragments that cannot be utilized by contiguous spectrum assignment algorithms. To obtain quantitative understanding of current spectrum utilization, we carried out a set of spectrum measurements in the 20MHz to 3GHz spectrum band at 4 locations concurrently in Guangdong province of China, and using these data sets we conducted a set of detailed analysis of the first and second order statistics of the collected data. Moreover, we also utilized such spectrum correlation to develop a 2-dimensional frequent pattern mining algorithm that can accurately predict channel availability based on past observations. For the multi-user multi-channel coordination issue, we present a new coordination approach subcarrier coding (SC), which was designed to enable the receiver obtain the coordination messages via simple energy detection. At last, for the application, we first propose deStress, the mobile and remote stress monitoring, alleviation and management system to quantitatively assesses the user’s stress level in a continuous range. deStress provides a system for stress monitoring and management, and a novel adaptive respiration-based bio-feedback approach to alleviate stress. Then we design and implement RASS, a portable real-time automatic sleep scoring system to accurately scores the sleeping state and detects sleep apnea in real-time based on the sensing results of pulse, blood oxygen, activity, sound and light signals. The above studies demonstrate that this thesis solves several key challenges of spectrum management and application in wireless and mobile networks.