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|dc.contributor.author||Sadhukhan, Samir K.|
|dc.description||Paul, Ayan, Bharat Sanchar Nigam Limited, 547B, Garia Garden, Marvel Castle, Kolkata 700084, India; Maitra, Madhubanti, Electrical Engineering Department, Jadavpur University, Kolkata, India; Mandal, Swarup, Wipro Technologies Limited, Kolkata, India; Sadhukhan, Samir K., MIS Group, Indian Institute of Management Calcutta, Kolkata, India; Saha, Debashish, MIS Group, Indian Institute of Management Calcutta, Kolkata, India|
|dc.description||ISSN/ISBN - 09521976|
|dc.description||DOI - 10.1016/j.engappai.2013.01.005|
|dc.description.abstract||Next generation wireless technologies offer various services from voice call to full motion pictures and even to high speed internet access. Consequently, the service providers (SP) armed with different wireless technologies (like 2.5G/3G/LTE) would require an adequate and significant amount of spectrum bandwidth for satisfying the need of their customers. Hence to achieve complete commercialization, the SPs, operating simultaneously, would demand for more and more spectrum from the regulatory body of the country. The spectrum demand on the part of the SP may vary with time (dynamic) because of varied kind of loads which are generated depending on the nature of the client-base, their requirements and their expected quality of experience. This work has addressed this challenging issue of allocating spectrum dynamically to different technologies under the portfolio of an SP. Here, we have conceived a scenario where service providers (SP) own multiple access networks (ANs) of different technologies. We envisage that an entity, called local spectrum controller (LSC) which is dedicated for managing the common pool of spectrum allocated to each SP. LSC is mainly responsible for distributing the spectrum to individual ANs of an SP in a fair manner. Since the available spectrum may not be sufficient enough to satisfy the aggregate demand from all ANs simultaneously, an LSC may face a situation, where satisfying individual demands from all ANs may result in a compromise between the demand and supply. This demand-supply situation would force an LSC or an SP to adhere to some dynamic spectrum management strategy, where demands of an AN would have to be satisfied depending on the current state of available spectrum and required usage of it. This calls for an adaptive dynamic strategy to be introduced by an SP for efficient spectrum distribution. The dynamic disparity of spectrum allocation can be idealized as a game between LSC and ANs. Hence, in the present work, we have modeled the problem of dynamic spectrum allocation as an n-player cooperative bankruptcy game and have solved the problem with the help of Shapley value and ?-value separately. We have investigated whether the ANs find it beneficial to cooperate with each other to make the solution sustainable enough. To evaluate the performances of the games that the ANs play, we have designed a novel utility function for each AN. We have identified plausible aims of an SP as minimizing overall dissatisfaction (MOD) and maximizing equality of distribution (MED). Next, we have studied performances of the above two solution concepts against max-min fairness algorithm (benchmarked in our case) with respect to the above objectives of LSC. Finally, we have proposed a unique heuristic in order to facilitate the decision making process of dynamic spectrum allocation, which leads to an adaptive yet optimized spectrum allocation strategy. � 2013 Elsevier Ltd.|
|dc.publisher||Engineering Applications of Artificial Intelligence|
|dc.subject||Cooperative game theory|
|dc.subject||Decision support system|
|dc.subject||Dynamic spectrum management|
|dc.title||A sustainable and collaborative strategy for dynamic spectrum management in next generation wireless networks|
|Appears in Collections:||Management Information Systems|
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