MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS

Bibliographic Details
Main Author:	Li, Shuang
Language:	English
Published:	The Ohio State University / OhioLINK 2013
Subjects:	Computer Engineering Computer Science
Online Access:	http://rave.ohiolink.edu/etdc/view?acc_num=osu1365089959

id	ndltd-OhioLink-oai-etd.ohiolink.edu-osu1365089959
record_format	oai_dc
collection	NDLTD
language	English
sources	NDLTD
topic	Computer Engineering Computer Science
spellingShingle	Computer Engineering Computer Science Li, Shuang MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS
author	Li, Shuang
author_facet	Li, Shuang
author_sort	Li, Shuang
title	MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS
title_short	MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS
title_full	MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS
title_fullStr	MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS
title_full_unstemmed	MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS
title_sort	managing dynamic spectrum access under uncertainty in cognitive radio networks
publisher	The Ohio State University / OhioLINK
publishDate	2013
url	http://rave.ohiolink.edu/etdc/view?acc_num=osu1365089959
work_keys_str_mv	AT lishuang managingdynamicspectrumaccessunderuncertaintyincognitiveradionetworks
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spelling	ndltd-OhioLink-oai-etd.ohiolink.edu-osu13650899592021-08-03T05:21:28Z MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS Li, Shuang Computer Engineering Computer Science Cognitive Radio Networks (CRNs) allow unlicensed users (secondary users, or SUs) to opportunistically access the licensed spectrum without causing disruptive interference to the primary users (PUs). One of the main challenges in CRNs is the ability to detect PU transmissions. Recent works have suggested the use of SU cooperation over individual sensing to improve sensing accuracy.Our overall goal is to manage dynamic spectrum access using cooperative sensing and provide provable performance guarantees. We have included the following in the thesis: We first consider a CRN consisting of multiple PUs and SUs to study the problem of maximizing the total expected system throughput. We propose a Bayesian decision-rule-based-algorithm to solve the problem optimally with a constant time complexity. To prioritize PU transmissions, we re-formulate the throughput maximization problem by adding a constraint on the PU throughput. The constrained optimization problem is shown to be strongly NP-hard and solved via a greedy algorithm with provable performance. We also investigate the case for which a constraint is put on the sensing time overhead, which limits the number of SUs that can participate in cooperative sensing. We reveal that the system throughput is monotonic over the number of SUs chosen for sensing.Second, we study the throughput maximization problem for a multichannel CRN where each SU can only sense a limited number of channels. We show that this problem is strongly NP-hard, and propose an approximation algorithm with a factor of at least 1/2*µ where µ is a system parameter reflecting the sensing capability of SUs across channels and their sensing budgets. This performance is achieved by exploiting a nice structural property of the objective function and constructing a particular matching.Third, we explore further into the operator based model and work on a social welfare maximization problem. To utilize spectrum resources in CRNs efficiently, an auction scheme is often applied where an operator serves as an auctioneer and accepts spectrum requests from SUs. Most existing works on spectrum auctions assume that the operator has perfect knowledge of PU activities. In practice, however, it is more likely that the operator only has statistical information of the PU traffic when it is trading a spectrum hole, and it is acquiring more accurate information in real time. We distinguish PU channels that are under the control of the operator, where accurate channel states are revealed in real-time, and channels that the operator acquires from PUs out of its control, where a sense-before-use paradigm has to be followed. Considering both spectrum uncertainty and sensing inaccuracy, we study the social welfare maximization problem for serving SUs with various levels of delay tolerance. We first model the problem as a finite horizon Markov decision process when the operator knows all spectrum requests in advance, and propose an optimal dynamic programming based algorithm. We then investigate the case when spectrum requests are submitted online, and propose a greedy algorithm that is 1/2-competitive for homogeneous channels and is comparable to the offline algorithm for more general settings. We further extend the online algorithm to an online auction scheme, which ensures incentive compatibility for the SUs and also provides a way for trading off social welfare and revenue.Fourth, we develop a distributed scheduling algorithm for SUs with i.i.d. arrival processes at PUs. Developing a distributed implementation that can fully utilize the spectrum opportunities for SUs has so far remained elusive. Although throughput optimal algorithms based on the well-known Maximal Weight Scheduling (MWS) algorithm exist for cognitive radio networks, they require central processing of network-wide SU information. We introduce a new distributed algorithm that asymptotically achieves the capacity region of the cognitive radio systems. Unlike existing distributed queue-length based CSMA/CA algorithms, the proposed algorithms achieve the full SU capacity region while adapting to the channel availability dynamics caused by unknown PU activity. 2013-07-11 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1365089959 http://rave.ohiolink.edu/etdc/view?acc_num=osu1365089959 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

MANAGING DYNAMIC SPECTRUM ACCESS UNDER UNCERTAINTY IN COGNITIVE RADIO NETWORKS

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