2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)最新文献

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Toward a Socially Optimal Wireless Spectrum Management 面向社会最优无线频谱管理
Zhen Li, Qi Liao, A. Striegel
{"title":"Toward a Socially Optimal Wireless Spectrum Management","authors":"Zhen Li, Qi Liao, A. Striegel","doi":"10.1109/SDR.2010.5507923","DOIUrl":"https://doi.org/10.1109/SDR.2010.5507923","url":null,"abstract":"It is widely recognized that the wireless spectrum is a scarce and limited resource and that the present practice of static spectrum allocation and exclusive licensing is inefficient. The proposed approaches generally either focus on maximization of spectrum utilization or profit maximization of individuals (such as the government or users). In this paper, we consider an efficient, or socially optimal, spectrum sharing that consists of three objectives: full (quantitative) utilization, effective (qualitative) utilization, and zero interference. Through a comparative study of these models using suggested objective criteria, we show a hybrid model consisting of a dynamic spectrum market and dynamic spectrum access supported by cognitive radio technologies that can achieve the social optimum. The dynamic spectrum market enabled by a benevolent social coordinator has fundamental differences from existing dynamic market models in that primary licensed user is not involved in the process of allocating underused spectrum. Moreover, the motivation of social coordinator is to reach socially optimal allocation of spectrum resources rather than to maximize profit or revenue of individuals.","PeriodicalId":236424,"journal":{"name":"2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131822228","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}
引用次数: 1
Cooperation Reliability Based on Reinforcement Learning for Cognitive Radio Networks 基于强化学习的认知无线电网络合作可靠性研究
N. Vucevic, I. Akyildiz, J. Pérez-Romero
{"title":"Cooperation Reliability Based on Reinforcement Learning for Cognitive Radio Networks","authors":"N. Vucevic, I. Akyildiz, J. Pérez-Romero","doi":"10.1109/SDR.2010.5507921","DOIUrl":"https://doi.org/10.1109/SDR.2010.5507921","url":null,"abstract":"The primary objective of cooperation in Cognitive Radio (CR) networks is to increase the efficiency and improve the network performance. However, CR users may act destructively and decrease both their own and others'' performances. This can be due to Byzantine adversaries or unintentional erroneous conduct in cooperation. This work presents an autonomous cooperation solution for each CR user, i.e., each CR user decides with whom to cooperate. The objective of the proposed solution is to increase the spectrum access in cooperative CR networks. To realize this, a Reinforcement Learning (RL) algorithm is utilized to determine the suitability of the available cooperators and select the appropriate set of cooperators. In addition, the proposed so-lution determines the most appropriate number of cooperators to achieve the highest efficiency for spectrum access. Accordingly, the control communication overhead is reduced. The simulation results demonstrate the learning capabilities of the proposed to achieve reliable behavior under highly unreliable conditions.","PeriodicalId":236424,"journal":{"name":"2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129334620","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}
引用次数: 9
Multi-Agent Q-Learning for Competitive Spectrum Access in Cognitive Radio Systems 认知无线电系统中竞争频谱接入的多智能体q学习
Husheng Li
{"title":"Multi-Agent Q-Learning for Competitive Spectrum Access in Cognitive Radio Systems","authors":"Husheng Li","doi":"10.1109/SDR.2010.5507919","DOIUrl":"https://doi.org/10.1109/SDR.2010.5507919","url":null,"abstract":"Resource allocation is an important issue in cognitive radio systems. It can be done by carrying out negotiation among secondary users. However, significant overhead may be incurred by the negotiation since the negotiation needs to be done frequently due to the rapid change of primary users' activity. In this paper, an Aloha-like spectrum access scheme without negotiation is considered for multi-user and multi-channel cognitive radio systems. To avoid collision incurred by the lack of coordination, each secondary user learns how to select channels according to its experience. Multi-agent reinforcement leaning (MARL) is applied in the framework of $Q$-learning by considering other secondary users as a part of the environment. A rigorous proof of the convergence of $Q$-learning is provided via the similarity between the $Q$-learning and Robinson-Monro algorithm, as well as the analysis of the corresponding ordinary differential equation (via Lyapunov function). The performance of learning (speed and gain in utility) is evaluated by numerical simulations.","PeriodicalId":236424,"journal":{"name":"2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125021685","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}
引用次数: 48
A Framework for Cooperative In-Band Sensing in Cognitive Radio Network 认知无线网络中协同带内感知框架
Ramzi R. Saifan, Yawen Wei, Y. Guan
{"title":"A Framework for Cooperative In-Band Sensing in Cognitive Radio Network","authors":"Ramzi R. Saifan, Yawen Wei, Y. Guan","doi":"10.1109/SDR.2010.5507922","DOIUrl":"https://doi.org/10.1109/SDR.2010.5507922","url":null,"abstract":"Many existing in-band sensing algorithms for CRNs adopted a periodic sensing/transmission architecture, where all the CR users do periodic sensing. Each periodic detection cycle is divided into two parts: sensing and transmission times. Sensing times are affected by many factors. In some worse scenarios (e.g., low SNRs), it may take more than half of the channel idle time for sensing. In this paper, we propose a new cooperative in-band sensing framework to increase sensing efficiency and robustness. In our framework, each CR operates in one of the two modes: Transmission and Sensing. The CRs that have data to send switch to Transmission Mode, provided that there is enough number of CR nodes in sensing mode. Therefore, CRs in transmission mode do not have to do any sensing during transmission, which imply that they can send for longer times. CRs in sensing mode send warning messages in case they detected the presence of PU. This cooperation (among CRs) is done on the same channel of transmission without the need for a CCC. Simulation and analytical results show that our sensing framework outperforms traditional sensing framework/approaches that require periodic sensing. At the end, we identify a set of important open problems to be addressed under this sensing framework.","PeriodicalId":236424,"journal":{"name":"2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091943","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}
引用次数: 3
Asymptotic Performance of ALOHA-Based Cognitive Overlaid Networks 基于aloha的认知覆盖网络的渐近性能
A. Banaei, C. Georghiades, Shuguang Cui
{"title":"Asymptotic Performance of ALOHA-Based Cognitive Overlaid Networks","authors":"A. Banaei, C. Georghiades, Shuguang Cui","doi":"10.1109/SDR.2010.5507927","DOIUrl":"https://doi.org/10.1109/SDR.2010.5507927","url":null,"abstract":"We study the asymptotic performance of two overlaid wireless ad-hoc networks that utilize the same temporal, spectral, and spatial resources based on random access schemes. The primary network consists of Poisson distributed legacy users with density $n$ and the secondary network consists of Poisson distributed cognitive radio users with density $m = n^{β}$ ($β > 1$) that utilize the spectrum opportunistically. Both networks are emph{decentralized} and deploy ALOHA protocols where the secondary users are equipped with range-limited emph{perfect} spectrum sensors to monitor and protect primary transmissions. First, we show that both networks can achieve their corresponding stand-alone throughput scaling even without secondary spectrum sensing (i.e., sensing range set to zero), which implies the need for a more comprehensive performance metric than just throughput scaling to evaluate the influence of the overlaid interactions. We thus introduce a new criterion, termed as the emph{asymptotic multiplexing gain}, which captures the effect of spectrum sensing and inter-network interferences.","PeriodicalId":236424,"journal":{"name":"2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133320956","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}
引用次数: 1
Interference Management in the TV White Space 电视空白区域的干扰管理
A. Sadek
{"title":"Interference Management in the TV White Space","authors":"A. Sadek","doi":"10.1109/SDR.2010.5507924","DOIUrl":"https://doi.org/10.1109/SDR.2010.5507924","url":null,"abstract":"One of the challenging problems in achieving reliable operation in the TV white space is interference. In this paper, the spectrum sharing problem between heterogeneous networks that are not interoperable is considered. Several non-cooperative interference management techniques are developed and analyzed. A generalization of dynamic frequency selection (DFS) that uses multiple channels to exploit the spatial variation of the interference pattern is developed. The new algorithm achieves significant performance gains compared to conventional DFS. Performance of multi-antenna interference cancellation techniques is studied. An interesting result on the limited gain of successive interference cancellation in a specific interference scenario is discussed.","PeriodicalId":236424,"journal":{"name":"2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127114951","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}
引用次数: 1
Towards a Real-Time Cognitive Radio Network Testbed: Architecture, Hardware Platform, and Application to Smart Grid 面向实时认知无线网络测试平台:体系结构、硬件平台及其在智能电网中的应用
R. Qiu, Zhe Chen, N. Guo, Yu Song, Peng Zhang, Husheng Li, L. Lai
{"title":"Towards a Real-Time Cognitive Radio Network Testbed: Architecture, Hardware Platform, and Application to Smart Grid","authors":"R. Qiu, Zhe Chen, N. Guo, Yu Song, Peng Zhang, Husheng Li, L. Lai","doi":"10.1109/SDR.2010.5507920","DOIUrl":"https://doi.org/10.1109/SDR.2010.5507920","url":null,"abstract":"A real-time cognitive radio network testbed is being built. This is the first paper to capture the overall picture of this project. Project scope and philosophy, design architecture, hardware platform, and key algorithms are reported. The use of cognitive radio network for smart grid is for the first time proposed in this paper. This unique testbed is ideal for such purpose.","PeriodicalId":236424,"journal":{"name":"2010 Fifth IEEE Workshop on Networking Technologies for Software Defined Radio Networks (SDR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129186451","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}
引用次数: 63
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