John M. Halloran

Distributed algorithm for collaborative detection in cognitive radio networks

A cognitive radio wireless network is investigated, in which a number of primary users (PUs) transmit in orthogonal frequency bands. There are also a number of secondary users (SUs) in the network, which monitor transmission opportunities in these frequency bands by collaboratively detecting whether each PU is transmitting. Each SU can participate in detecting only one PUs transmission at a time although it may locate in multiple PUs detection ranges. A network management issue is studied, which addresses the best assignment of SUs to detecting PUs so that the overall probability of detection error is minimized. A distributed implementation of the elimination algorithm is proposed to efficiently find the best assignment by drawing connection between the current problem and the inference problem in the context of probabilistic graphic models. The graphic representation of the problem is also discussed.

Simulation analysis of financial risks for three vegetable crops in Hawaii

Historical data on yields, input and output prices of three vegetable crops in Hawaii are analyzed. Appropriate theoretical probability distributions are fitted to these data to capture their randomness for profit simulation. Stochastic dominance analysis is then performed using the simulated profit data to rank the profitability of the three crops. Under the assumption that the producer is risk averse, growing lettuce appears to be more preferable to head cabbage, and head cabbage more preferable to mustard cabbage.