Pub Date : 2010-04-06DOI: 10.1109/DYSPAN.2010.5457869
H. Karimi, G. Lapierre, T. O’Leary, W. Sami, G. Warren, Martin Fenton
NA
{"title":"Block Edge Mask Baseline Limits for Mobile Communication Network Base Stations in the 790-862 MHz Digital Dividend Spectrum","authors":"H. Karimi, G. Lapierre, T. O’Leary, W. Sami, G. Warren, Martin Fenton","doi":"10.1109/DYSPAN.2010.5457869","DOIUrl":"https://doi.org/10.1109/DYSPAN.2010.5457869","url":null,"abstract":"NA","PeriodicalId":106204,"journal":{"name":"2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115111865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-04-06DOI: 10.1109/DYSPAN.2010.5457833
M. Buddhikot
In year 2007, out of 2.85 billion cellular network users world-wide, only 295 million i.e. approximately 10% used high speed mobile data services. In the next few years, with rapid adoption of smart phones that allow end-users any-time, any-where Internet access, mobile data traffic is expected to increase exponentially. The wireless service providers face two main challenges as they address this new trend: (1) as the peruser throughput requirements scale to multi-Mbps, how to scale the networks to achieve dramatic improvements in wireless access and system capacity, and (2) in the face of declining ARPU and increasing competition, how to reduce cost of deploying and operating the network. In this paper, we highlight how cognitive radio technologies, specifically Dynamic Spectrum Access (DSA) and Self-X will help meet these challenges and usher in a new transformation in cellular networks. We discuss in detail technologies in the following key areas: (1) DSA for capacity augmentation in macrocells, (2) Ultra-broadband small and femto cells using spectrum white spaces, (3) Self-X (X=configure, monitor, diagnose, repair and optimize) for LTE networks, and (4) Energy management. We show that the application of cognitive radio ideas to infrastructure cellular networks can bring great benefits by achieving a balance between complexity, practical realizability, performance gains and true market potential.
{"title":"Cognitive Radio, DSA and Self-X: Towards Next Transformation in Cellular Networks (Extended Abstract)","authors":"M. Buddhikot","doi":"10.1109/DYSPAN.2010.5457833","DOIUrl":"https://doi.org/10.1109/DYSPAN.2010.5457833","url":null,"abstract":"In year 2007, out of 2.85 billion cellular network users world-wide, only 295 million i.e. approximately 10% used high speed mobile data services. In the next few years, with rapid adoption of smart phones that allow end-users any-time, any-where Internet access, mobile data traffic is expected to increase exponentially. The wireless service providers face two main challenges as they address this new trend: (1) as the peruser throughput requirements scale to multi-Mbps, how to scale the networks to achieve dramatic improvements in wireless access and system capacity, and (2) in the face of declining ARPU and increasing competition, how to reduce cost of deploying and operating the network. In this paper, we highlight how cognitive radio technologies, specifically Dynamic Spectrum Access (DSA) and Self-X will help meet these challenges and usher in a new transformation in cellular networks. We discuss in detail technologies in the following key areas: (1) DSA for capacity augmentation in macrocells, (2) Ultra-broadband small and femto cells using spectrum white spaces, (3) Self-X (X=configure, monitor, diagnose, repair and optimize) for LTE networks, and (4) Energy management. We show that the application of cognitive radio ideas to infrastructure cellular networks can bring great benefits by achieving a balance between complexity, practical realizability, performance gains and true market potential.","PeriodicalId":106204,"journal":{"name":"2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132761530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-04-01DOI: 10.1109/DYSPAN.2010.5457857
Yi Gai, B. Krishnamachari, Rahul Jain
We consider the following fundamental problem in the context of channelized dynamic spectrum access. There are $M$ secondary users and $N ge M$ orthogonal channels. Each secondary user requires a single channel for operation that does not conflict with the channels assigned to the other users. Due to geographic dispersion, each secondary user can potentially see different primary user occupancy behavior on each channel. Time is divided into discrete decision rounds. The throughput obtainable from spectrum opportunities on each user-channel combination over a decision period is modeled as an arbitrarily-distributed non-negative random variable with bounded support but unknown mean, i.i.d. over time. The objective is to search for an allocation of channels for all users that maximizes the expected sum throughput. We formulate this problem as a combinatorial multi-armed bandit (MAB), in which each arm corresponds to a matching of the users to channels. Unlike most prior work on multi-armed bandits, this combinatorial formulation results in dependent arms. Moreover, the number of arms grows super-exponentially as the permutation $P(N,M)$. We present a novel matching-learning algorithm with polynomial storage and polynomial computation per decision period for this problem, and prove that it results in a regret (the gap between the expected sum-throughput obtained by a genie-aided perfect allocation and that obtained by this algorithm) that is uniformly upper-bounded for all time $n$ by a function that grows as $O(M^4 N log n)$, i.e. polynomial in the number of unknown parameters and logarithmic in time. We also discuss how our results provide a non-trivial generalization of known theoretical results on multi-armed bandits.
在信道化动态频谱接入的背景下，我们考虑以下基本问题。有$M$次用户和$N ge M$正交信道。每个辅助用户需要一个单独的通道进行操作，该通道与分配给其他用户的通道不冲突。由于地理上的分散，每个辅助用户可能在每个信道上看到不同的主用户占用行为。时间被划分为离散的决策轮。在一个决策周期内，从每个用户信道组合的频谱机会中获得的吞吐量被建模为具有有限支持但均值未知的任意分布的非负随机变量，i.i.d.随时间变化。目标是为所有用户搜索通道分配，使期望的总吞吐量最大化。我们将此问题表述为组合多臂强盗(MAB)，其中每条手臂对应于用户与信道的匹配。与大多数先前的多臂强盗工作不同，这种组合公式导致依赖臂。此外，臂的数量随着P(N,M)的排列呈指数级增长。针对这一问题，我们提出了一种具有多项式存储和多项式决策周期计算的匹配学习算法，并通过一个增长为$O(M^4 n log n)$的函数证明了该算法在所有时间$n$上都是一致上界的遗憾(由基因辅助完美分配获得的期望总吞吐量与该算法获得的期望总吞吐量之间的差距)，即未知参数数量的多项式和时间的对数。我们还讨论了我们的结果如何为已知的多武装强盗理论结果提供了一个非平凡的推广。
{"title":"Learning Multiuser Channel Allocations in Cognitive Radio Networks: A Combinatorial Multi-Armed Bandit Formulation","authors":"Yi Gai, B. Krishnamachari, Rahul Jain","doi":"10.1109/DYSPAN.2010.5457857","DOIUrl":"https://doi.org/10.1109/DYSPAN.2010.5457857","url":null,"abstract":"We consider the following fundamental problem in the context of channelized dynamic spectrum access. There are $M$ secondary users and $N ge M$ orthogonal channels. Each secondary user requires a single channel for operation that does not conflict with the channels assigned to the other users. Due to geographic dispersion, each secondary user can potentially see different primary user occupancy behavior on each channel. Time is divided into discrete decision rounds. The throughput obtainable from spectrum opportunities on each user-channel combination over a decision period is modeled as an arbitrarily-distributed non-negative random variable with bounded support but unknown mean, i.i.d. over time. The objective is to search for an allocation of channels for all users that maximizes the expected sum throughput. We formulate this problem as a combinatorial multi-armed bandit (MAB), in which each arm corresponds to a matching of the users to channels. Unlike most prior work on multi-armed bandits, this combinatorial formulation results in dependent arms. Moreover, the number of arms grows super-exponentially as the permutation $P(N,M)$. We present a novel matching-learning algorithm with polynomial storage and polynomial computation per decision period for this problem, and prove that it results in a regret (the gap between the expected sum-throughput obtained by a genie-aided perfect allocation and that obtained by this algorithm) that is uniformly upper-bounded for all time $n$ by a function that grows as $O(M^4 N log n)$, i.e. polynomial in the number of unknown parameters and logarithmic in time. We also discuss how our results provide a non-trivial generalization of known theoretical results on multi-armed bandits.","PeriodicalId":106204,"journal":{"name":"2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126092589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-03-29DOI: 10.1109/DYSPAN.2010.5457903
Lingjie Duan, Jianwei Huang, Biying Shou
Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.
{"title":"Competition with Dynamic Spectrum Leasing","authors":"Lingjie Duan, Jianwei Huang, Biying Shou","doi":"10.1109/DYSPAN.2010.5457903","DOIUrl":"https://doi.org/10.1109/DYSPAN.2010.5457903","url":null,"abstract":"Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.","PeriodicalId":106204,"journal":{"name":"2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121431201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-08-15DOI: 10.1109/MCOM.2011.5723799
C. Caicedo, M. Weiss
Spectrum trading markets are of growing interest to many spectrum management agencies. They are motivated by their desire to increase the use of market based mechanisms for spectrum management and reduce their emphasis on command and control methods. Despite the liberalization of regulations on spectrum trading in some countries, spectrum markets have not yet emerged as a key spectrum assignment component. The lack of liquidity in these markets is sometimes cited as a primary factor in this outcome. This work focuses on determining the conditions for viability of spectrum trading markets by considering scenarios with different market structures, number of trading participants and amount of tradable spectrum. We make use of Agent-Based Computational Economics (ACE) to analyze each market scenario and the behaviors of its participants. Our models indicate that spectrum markets can be viable in a service if sufficient numbers of market participants exist and the amount of tradable spectrum is balanced to the demand. We use the results of this analysis and the characteristics of the viable markets found to make recommendations for the design of spectrum trading markets. Further work will explore more complicated scenarios.
{"title":"The Viability of Spectrum Trading Markets","authors":"C. Caicedo, M. Weiss","doi":"10.1109/MCOM.2011.5723799","DOIUrl":"https://doi.org/10.1109/MCOM.2011.5723799","url":null,"abstract":"Spectrum trading markets are of growing interest to many spectrum management agencies. They are motivated by their desire to increase the use of market based mechanisms for spectrum management and reduce their emphasis on command and control methods. Despite the liberalization of regulations on spectrum trading in some countries, spectrum markets have not yet emerged as a key spectrum assignment component. The lack of liquidity in these markets is sometimes cited as a primary factor in this outcome. This work focuses on determining the conditions for viability of spectrum trading markets by considering scenarios with different market structures, number of trading participants and amount of tradable spectrum. We make use of Agent-Based Computational Economics (ACE) to analyze each market scenario and the behaviors of its participants. Our models indicate that spectrum markets can be viable in a service if sufficient numbers of market participants exist and the amount of tradable spectrum is balanced to the demand. We use the results of this analysis and the characteristics of the viable markets found to make recommendations for the design of spectrum trading markets. Further work will explore more complicated scenarios.","PeriodicalId":106204,"journal":{"name":"2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129366493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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