3,885 research outputs found
Cross-Layer Optimization and Dynamic Spectrum Access for Distributed Wireless Networks
We proposed a novel spectrum allocation approach for distributed cognitive radio networks. Cognitive radio systems are capable of sensing the prevailing environmental conditions and automatically adapting its operating parameters in order to enhance system and network performance. Using this technology, our proposed approach optimizes each individual wireless device and its single-hop communication links using the partial operating parameter and environmental information from adjacent devices within the wireless network. Assuming stationary wireless nodes, all wireless communication links employ non-contiguous orthogonal frequency division multiplexing (NC-OFDM) in order to enable dynamic spectrum access (DSA). The proposed approach will attempt to simultaneously minimize the bit error rate, minimize out-of-band (OOB) interference, and maximize overall throughput using a multi-objective fitness function. Without loss in generality, genetic algorithms are employed to perform the actual optimization. Two generic optimization approaches, subcarrier-wise approach and block-wise approach, were proposed to access spectrum. We also proposed and analyzed several approaches implemented via genetic algorithms (GA), such as quantizing variables, using adaptive variable ranges, and Multi-Objective Genetic Algorithms, for increasing the speed and improving the results of combined spectrum utilization/cross-layer optimization approaches proposed, together with several assisting processes and modifications devised to make the optimization to improve efficiency and execution time
Cognitive Access Policies under a Primary ARQ process via Forward-Backward Interference Cancellation
This paper introduces a novel technique for access by a cognitive Secondary
User (SU) using best-effort transmission to a spectrum with an incumbent
Primary User (PU), which uses Type-I Hybrid ARQ. The technique leverages the
primary ARQ protocol to perform Interference Cancellation (IC) at the SU
receiver (SUrx). Two IC mechanisms that work in concert are introduced: Forward
IC, where SUrx, after decoding the PU message, cancels its interference in the
(possible) following PU retransmissions of the same message, to improve the SU
throughput; Backward IC, where SUrx performs IC on previous SU transmissions,
whose decoding failed due to severe PU interference. Secondary access policies
are designed that determine the secondary access probability in each state of
the network so as to maximize the average long-term SU throughput by
opportunistically leveraging IC, while causing bounded average long-term PU
throughput degradation and SU power expenditure. It is proved that the optimal
policy prescribes that the SU prioritizes its access in the states where SUrx
knows the PU message, thus enabling IC. An algorithm is provided to optimally
allocate additional secondary access opportunities in the states where the PU
message is unknown. Numerical results are shown to assess the throughput gain
provided by the proposed techniques.Comment: 16 pages, 11 figures, 2 table
Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
This article provides an overview of the state-of-art results on
communication resource allocation over space, time, and frequency for emerging
cognitive radio (CR) wireless networks. Focusing on the
interference-power/interference-temperature (IT) constraint approach for CRs to
protect primary radio transmissions, many new and challenging problems
regarding the design of CR systems are formulated, and some of the
corresponding solutions are shown to be obtainable by restructuring some
classic results known for traditional (non-CR) wireless networks. It is
demonstrated that convex optimization plays an essential role in solving these
problems, in a both rigorous and efficient way. Promising research directions
on interference management for CR and other related multiuser communication
systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex
optimization for signal processin
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