Parallelism with limited nondeterminism

Computational complexity theory studies which computational problems can be solved with limited access to resources. The past fifty years have seen a focus on the relationship between intractable problems and efficient algorithms. However, the relationship between inherently sequential problems and highly parallel algorithms has not been as well studied. Are there efficient but inherently sequential problems that admit some relaxed form of highly parallel algorithm? In this dissertation, we develop the theory of structural complexity around this relationship for three common types of computational problems. Specifically, we show tradeoffs between time, nondeterminism, and parallelizability. By clearly defining the notions and complexity classes that capture our intuition for parallelizable and sequential problems, we create a comprehensive framework for rigorously proving parallelizability and non-parallelizability of computational problems. This framework provides the means to prove whether otherwise tractable problems can be effectively parallelized, a need highlighted by the current growth of multiprocessor systems. The views adopted by this dissertation—alternate approaches to solving sequential problems using approximation, limited nondeterminism, and parameterization—can be applied practically throughout computer science

Experimental study of cognitive radio test-bed using USRP

Cognitive Radio is an emerging technology that enables efficient utilization of the spectrum. As such, it has created great interests in industrial and research fields. Many people have proposed test-bed models for the performance analysis of primary and secondary users in a real-time noise environment. However, these test-beds are generally lacking in their range of capabilities as well as accurate implementation of the proposed models. In this thesis, we develop our test-bed on USRP to achieve the spectrum sensing and co-existence of primary and secondary users, while implementing the rendezvous protocols for secondary traffic coordination. We first demonstrate the spectrum sensing on the primary users using an energy detector(Average periodogram analysis) to obtain the average power of the primary channel under two different channel conditions (busy or idle). The focus is extended on developing the Markov traffic model and the Coded OFDM transceivers, while discussing the practical limitations for Markov traffic and viable solutions for reducing the burst errors for Coded OFDM. Finally, a four-node test-bed model of primary and secondary users is analyzed with the interference metrics (packet loss and error rate) for different scenarios. Also, the throughput and the interference metrics are compared for different rendezvous protocols of the secondary users