On the optimization problems in multiaccess communication systems

In a communication system, the bandwidth is often a primary resource. In order to support concurrent access by numerous users in a network, this finite and expensive resource must be shared among many independent contending users. Multi-access protocols control this access of the resource among users to achieve its efficient utilization, satisfy connectivity requirements and resolve any conflict among the contending users. Many optimization problems arise in designing a multi-access protocol. Among these, there is a class of optimization problems known as NP-complete, and no polynomial algorithm can possibly solve them. Conventional methods may not be efficient arid often produce poor solutions. In this dissertation, we propose a neural network-based algorithm for solving NP-complete problems encountered in multi-access communication systems. Three combinatorial optimization problems have been solved by the proposed algorithms; namely, frame pattern design in integrated TDMA communication networks, optimal broadcast scheduling in multihop packet radio networks, and optimal channel assignment in FDM A mobile communication networks. Numerical studies have shown encouraging results in searching for the global optimal solutions by using this algorithm. The determination of the related parameters regarding convergence and solution quality is investigated in this dissertation. Performance evaluations and comparisons with other algorithms have been performed

In Defense of Wireless Carrier Sense

Carrier sense is often used to regulate concurrency in wireless medium access control (MAC) protocols, balancing interference protection and spatial reuse. Carrier sense is known to be imperfect, and many improved techniques have been proposed. Is the search for a replacement justified? This paper presents a theoretical model for average case two-sender carrier sense based on radio propagation theory and Shannon capacity. Analysis using the model shows that carrier sense performance is surprisingly close to optimal for radios with adaptive bitrate. The model suggests that hidden and exposed terminals usually cause modest reductions in throughput rather than dramatic decreases. Finally, it is possible to choose a fixed sense threshold which performs well across a wide range of scenarios, in large part due to the role of the noise floor. Experimental results from an indoor 802.11 testbed support these claims

Remote monitoring and control of autonomous underwater vehicles

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1997.Includes bibliographical references (leaves 111-113).by John H.I. Kim.M.S

Decentralized sequential change detection using physical layer fusion

The problem of decentralized sequential detection with conditionally independent observations is studied. The sensors form a star topology with a central node called fusion center as the hub. The sensors make noisy observations of a parameter that changes from an initial state to a final state at a random time where the random change time has a geometric distribution. The sensors amplify and forward the observations over a wireless Gaussian multiple access channel and operate under either a power constraint or an energy constraint. The optimal transmission strategy at each stage is shown to be the one that maximizes a certain Ali-Silvey distance between the distributions for the hypotheses before and after the change. Simulations demonstrate that the proposed analog technique has lower detection delays when compared with existing schemes. Simulations further demonstrate that the energy-constrained formulation enables better use of the total available energy than the power-constrained formulation in the change detection problem.Comment: 10 pages, two-column, 10 figures, revised based on feedback from reviewers, accepted for publication in IEEE Trans. on Wireless Communication