Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR Constraints
Recently, there have been some research works in the design of cross-layer protocols for cognitive radio (CR) networks, where the Protocol Model is used to model the radio interference. In this paper we consider a multihop multi-channel CR network. We use a more realistic Signal-to-Interference-plus...
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| Format: | Article |
| Language: | English |
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Wiley
2010-01-01
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| Series: | International Journal of Digital Multimedia Broadcasting |
| Online Access: | http://dx.doi.org/10.1155/2010/985458 |
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| _version_ | 1832561095115538432 |
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| author | Miao Ma Danny H. K. Tsang |
| author_facet | Miao Ma Danny H. K. Tsang |
| author_sort | Miao Ma |
| collection | DOAJ |
| description | Recently, there have been some research works in the design of cross-layer protocols for cognitive radio (CR) networks, where the Protocol Model is used to model the radio interference. In this paper we consider a multihop multi-channel CR network. We use a more realistic Signal-to-Interference-plus-Noise Ratio (SINR) model for radio interference and study the following cross-layer throughput optimization problem: (1) Given a set of secondary users with random but fixed location, and a set of traffic flows, what is the max-min achievable throughput? (2) To achieve the optimum, how to choose the set of active links, how to assign the channels to each active link, and how to route the flows? To the end, we present a formal mathematical formulation with the objective of maximizing the minimum end-to-end flow throughput. Since the formulation is in the forms of mixed integer nonlinear programming (MINLP), which is generally a hard problem, we develop a heuristic method by solving a relaxation of the original problem, followed by rounding and simple local optimization. Simulation results show that the heuristic approach performs very well, that is, the solutions obtained by the heuristic are very close to the global optimum obtained via LINGO. |
| format | Article |
| id | doaj-art-7be948d40d664799953ada31dc062974 |
| institution | Kabale University |
| issn | 1687-7578 1687-7586 |
| language | English |
| publishDate | 2010-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Digital Multimedia Broadcasting |
| spelling | doaj-art-7be948d40d664799953ada31dc0629742025-02-03T01:25:59ZengWileyInternational Journal of Digital Multimedia Broadcasting1687-75781687-75862010-01-01201010.1155/2010/985458985458Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR ConstraintsMiao Ma0Danny H. K. Tsang1Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong KongDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong KongRecently, there have been some research works in the design of cross-layer protocols for cognitive radio (CR) networks, where the Protocol Model is used to model the radio interference. In this paper we consider a multihop multi-channel CR network. We use a more realistic Signal-to-Interference-plus-Noise Ratio (SINR) model for radio interference and study the following cross-layer throughput optimization problem: (1) Given a set of secondary users with random but fixed location, and a set of traffic flows, what is the max-min achievable throughput? (2) To achieve the optimum, how to choose the set of active links, how to assign the channels to each active link, and how to route the flows? To the end, we present a formal mathematical formulation with the objective of maximizing the minimum end-to-end flow throughput. Since the formulation is in the forms of mixed integer nonlinear programming (MINLP), which is generally a hard problem, we develop a heuristic method by solving a relaxation of the original problem, followed by rounding and simple local optimization. Simulation results show that the heuristic approach performs very well, that is, the solutions obtained by the heuristic are very close to the global optimum obtained via LINGO.http://dx.doi.org/10.1155/2010/985458 |
| spellingShingle | Miao Ma Danny H. K. Tsang Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR Constraints International Journal of Digital Multimedia Broadcasting |
| title | Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR Constraints |
| title_full | Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR Constraints |
| title_fullStr | Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR Constraints |
| title_full_unstemmed | Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR Constraints |
| title_short | Cross-Layer Throughput Optimization in Cognitive Radio Networks with SINR Constraints |
| title_sort | cross layer throughput optimization in cognitive radio networks with sinr constraints |
| url | http://dx.doi.org/10.1155/2010/985458 |
| work_keys_str_mv | AT miaoma crosslayerthroughputoptimizationincognitiveradionetworkswithsinrconstraints AT dannyhktsang crosslayerthroughputoptimizationincognitiveradionetworkswithsinrconstraints |