搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

认知无线电网络中基于抢占式排队论的频谱切换模型

杨小龙 谭学治 关凯

引用本文:
Citation:

认知无线电网络中基于抢占式排队论的频谱切换模型

杨小龙, 谭学治, 关凯

Spectrum handoff model based on preemptive queuing theory in cognitive radio networks

Yang Xiao-Long, Tan Xue-Zhi, Guan Kai
PDF
导出引用
  • 针对认知无线电网络中认知用户广义传输时间的优化问题, 提出了一种基于抢占式续传优先权M/G/m排队理论的频谱切换模型. 在该排队模型中, 为了最小化认知用户广义传输时间, 采用混合排队-并列式服务的排队方式. 在此基础上, 深入分析多个认知用户、多个授权信道、多次频谱切换条件下认知用户信道使用情况, 从而推导出广义传输时间表达式. 最后探讨了该模型下自适应频谱切换策略. 仿真结果表明, 相比于已有的频谱切换模型, 该模型不仅能够更加完整地描述认知用户频谱切换行为, 而且使得认知用户传输时延更小, 广义传输时间更短. 此外, 认知无线电网络允许的认知用户服务强度增加, 能够容纳的认知用户数量增多. 因此, 该模型提升了认知用户频谱切换的性能, 更好地实现了认知用户与授权用户的频谱共享.
    Cognitive radio can significantly improve spectrum efficiency by temporarily sharing under-utilized licensed frequency with primary users. Its spectrum management framework consists of four parts: spectrum sensing, spectrum decision, spectrum sharing and spectrum handoff. The last part is what we focus on in this paper. Spectrum handoff, which aims at guaranteeing requirement for service of secondary users and shortening time delay produced by interruption from primary users, is an important functionality of cognitive radio networks. For solving the problem of optimizing the extended data delivery time, a spectrum handoff model is proposed based on the preemptive resume priority M/G/m queuing theory. In order to minimize the extended data delivery time, the queuing method with mixed queuing and parallel service is adopted. In this model, each channel has its own high-priority queue and there is only one low-priority queue for all secondary users. The primary and secondary users respectively enter into the high-priority and low-priority queue to establish corresponding primary connections and secondary connections and execute corresponding data transmission. On the above basis, secondary users’ channel usage behaviors are thoroughly analyzed in the cases of multiple secondary users, multiple licensed channels and multiple spectrum handoffs. In this process, when multiple interruptions occur, the secondary user will stay on the current channel and suspend data transmission until primary users finish their data transmission, otherwise the secondary user will switch from the current channel to the predetermined target channel to resume his unfinished data transmission. The target channel is sequentially obtained from the target channel sequence, which is determined by channel parameter estimation algorithm. Based on the analysis of channel usage behaviors for secondary users, the total time delay caused by spectrum handoffs within the whole data transmission process is derived first. The total time delay can be deduced from two scenarios. One is that the target channel is the current channel. For this reason, the total time delay equals transmission time of primary users in high-priority queue. Obviously, the other is that the target channel is not the current channel. Thus, the total time delay equals the sum of transmission times of primary users in high-priority and secondary users ahead in low-priority. In addition, appearance of new primary users should also be considered in the data transmission process. Then, expressions of the extended data delivery time in two different cases (i. e. always-staying strategy and always-changing strategy) are respectively derived. Furthermore, the adaptive spectrum handoff strategy is finally discussed, which is to choose the optimal scheme from always-staying and always-changing strategy when a spectrum handoff happens. Simulation results verify that this model can not only describe handoff behaviors of secondary users more perfectly, but also can make the transmission time delay smaller and make the extended data delivery time shorter than the existing spectrum handoff model. Especially, with the increase of service intensity of primary users, the advantages of the proposed spectrum handoff model are more outstanding. In addition, the allowable secondary user service intensity is improved and the receptive number of secondary user is increased in cognitive radio networks. All in all, the proposed spectrum handoff model improves the performance of spectrum handoff, increases the capacity of cognitive radio networks and optimally realizes spectrum sharing between secondary users and primary users.
    • 基金项目: 国家自然科学基金(批准号: 61071104)和国家科技重大专项(批准号: 2011ZX03004-006) 资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61071104), and the National Science and Technology Major Project of the Ministry of Science and Technology of China (Grant No. 2011ZX03004-006).
    [1]

    Wang B B, Liu K J R 2011 IEEE J. Sel. Topics Signal Process. 5 5

    [2]

    Wang L C, Wang C W, Chang C J 2012 IEEE Trans. Commun. 60 2444

    [3]

    Li Q C, Niu H N, Papathanassiou A T, Wu G 2014 IEEE Veh. Technol. Mag. 9 71

    [4]

    Bhushan N, Li J Y, Malladi D, Gilmore R, Brenner D, Damnjanovic A, Sukhavasi R, Patel C, Geirhofe S 2014 IEEE Commun. Mag. 52 82

    [5]

    Zu Y X, Zhou J, Zeng C C 2010 Chin. Phys. B 19 119501

    [6]

    Zhang X J, Lu Y, Tian F, Sun Z X, Cheng X F 2014 Acta Phys. Sin. 63 078401 (in Chinese) [张学军, 鲁友, 田峰, 孙知信, 成谢锋 2014 物理学报 63 078401]

    [7]

    Zu Y X, Zhou J 2012 Chin. Phys. B 21 019501

    [8]

    Gavrilovska L, Atanasovski V, Macaluso I, DaSilva L A 2013 IEEE Commun. Surveys Tut. 15 1761

    [9]

    Qi P H, Li Z, Si J B, Gao R 2014 Chin. Phys. B 23 128401

    [10]

    Bansal T, Li D, Sinha P 2014 IEEE Trans. Mobile Comput. 13 852

    [11]

    Chai Z Y, Wang B, Li Y L 2014 Acta Phys. Sin. 63 228802 (in Chinese) [柴争义, 王秉, 李亚伦 2014 物理学报 63 228802]

    [12]

    Christian I, Moh S, Chung I, Lee J Y 2012 IEEE Commun. Mag. 50 114

    [13]

    Msumba J A, Xu H 2013 IEEE Africon 2013 Mauritius, Sept. 9-12, 2013 p1

    [14]

    Romero J, Sallent O, Umbert A 2013 IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications London, United Kingdom Sept. 8-11, 2013 p2512

    [15]

    Li C P, Neely M J 2011 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks Princeton, New Jersey May 9-13, 2011 p401

    [16]

    Xu Y H, Anpalagan A, Wu Q H, Shen L, Gao Z, Wang J L 2013 IEEE Commun. Surveys Tut. 15 1689

    [17]

    Li X, Zhao Q H, Guan X H, Tong L 2011 IEEE J. Sel. Areas Commun. 29 746

    [18]

    Nejatian S, Syed-Yusof S K, Latiff N M A, Asadpour V 2013 IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications London, United Kingdom Sept. 8-11, 2013 p2887

    [19]

    Liu J, Chen W, Cao Z, Zhang Y J 2012 IET Communications 6 945

    [20]

    Wang J, Huang A P, Wang W, Quek T Q S 2013 IEEE Wireless Commun. Lett. 2 175

    [21]

    Wang L C, Wang C W, Chang C J 2012 IEEE Trans. Mobile Comput. 11 1499

    [22]

    Wang C W, Wang L C 2012 IEEE J. Sel. Areas Commun. 30 2016

    [23]

    Liu Y, Tamma B R, Manoj B S, Rao R 2010 INFOCOM IEEE Conference on Computer Communications Workshops San Diego, USA March 15-19, 2010 p1

    [24]

    Wu C, Jiang H, You X J 2014 Acta Phys. Sin. 63 088801 (in Chinese) [伍春, 江虹, 尤晓建 2014 物理学报 63 088801]

    [25]

    Bose S K 2002 An Introduction to Queuing Systems (New York: Kluwer Academic/Plenum) pp168-169

  • [1]

    Wang B B, Liu K J R 2011 IEEE J. Sel. Topics Signal Process. 5 5

    [2]

    Wang L C, Wang C W, Chang C J 2012 IEEE Trans. Commun. 60 2444

    [3]

    Li Q C, Niu H N, Papathanassiou A T, Wu G 2014 IEEE Veh. Technol. Mag. 9 71

    [4]

    Bhushan N, Li J Y, Malladi D, Gilmore R, Brenner D, Damnjanovic A, Sukhavasi R, Patel C, Geirhofe S 2014 IEEE Commun. Mag. 52 82

    [5]

    Zu Y X, Zhou J, Zeng C C 2010 Chin. Phys. B 19 119501

    [6]

    Zhang X J, Lu Y, Tian F, Sun Z X, Cheng X F 2014 Acta Phys. Sin. 63 078401 (in Chinese) [张学军, 鲁友, 田峰, 孙知信, 成谢锋 2014 物理学报 63 078401]

    [7]

    Zu Y X, Zhou J 2012 Chin. Phys. B 21 019501

    [8]

    Gavrilovska L, Atanasovski V, Macaluso I, DaSilva L A 2013 IEEE Commun. Surveys Tut. 15 1761

    [9]

    Qi P H, Li Z, Si J B, Gao R 2014 Chin. Phys. B 23 128401

    [10]

    Bansal T, Li D, Sinha P 2014 IEEE Trans. Mobile Comput. 13 852

    [11]

    Chai Z Y, Wang B, Li Y L 2014 Acta Phys. Sin. 63 228802 (in Chinese) [柴争义, 王秉, 李亚伦 2014 物理学报 63 228802]

    [12]

    Christian I, Moh S, Chung I, Lee J Y 2012 IEEE Commun. Mag. 50 114

    [13]

    Msumba J A, Xu H 2013 IEEE Africon 2013 Mauritius, Sept. 9-12, 2013 p1

    [14]

    Romero J, Sallent O, Umbert A 2013 IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications London, United Kingdom Sept. 8-11, 2013 p2512

    [15]

    Li C P, Neely M J 2011 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks Princeton, New Jersey May 9-13, 2011 p401

    [16]

    Xu Y H, Anpalagan A, Wu Q H, Shen L, Gao Z, Wang J L 2013 IEEE Commun. Surveys Tut. 15 1689

    [17]

    Li X, Zhao Q H, Guan X H, Tong L 2011 IEEE J. Sel. Areas Commun. 29 746

    [18]

    Nejatian S, Syed-Yusof S K, Latiff N M A, Asadpour V 2013 IEEE 24th International Symposium on Personal Indoor and Mobile Radio Communications London, United Kingdom Sept. 8-11, 2013 p2887

    [19]

    Liu J, Chen W, Cao Z, Zhang Y J 2012 IET Communications 6 945

    [20]

    Wang J, Huang A P, Wang W, Quek T Q S 2013 IEEE Wireless Commun. Lett. 2 175

    [21]

    Wang L C, Wang C W, Chang C J 2012 IEEE Trans. Mobile Comput. 11 1499

    [22]

    Wang C W, Wang L C 2012 IEEE J. Sel. Areas Commun. 30 2016

    [23]

    Liu Y, Tamma B R, Manoj B S, Rao R 2010 INFOCOM IEEE Conference on Computer Communications Workshops San Diego, USA March 15-19, 2010 p1

    [24]

    Wu C, Jiang H, You X J 2014 Acta Phys. Sin. 63 088801 (in Chinese) [伍春, 江虹, 尤晓建 2014 物理学报 63 088801]

    [25]

    Bose S K 2002 An Introduction to Queuing Systems (New York: Kluwer Academic/Plenum) pp168-169

  • [1] 柴争义, 王秉, 李亚伦. 拟态物理学优化的认知无线电网络频谱分配. 物理学报, 2014, 63(22): 228802. doi: 10.7498/aps.63.228802
    [2] 张耀利, 吴保卫, 王月娥, 韩晓霞. 切换奇异系统的有限时间稳定. 物理学报, 2014, 63(17): 170205. doi: 10.7498/aps.63.170205
    [3] 郑仕链, 杨小牛, 赵知劲. 用于随机解调器压缩采样的重构判定方法. 物理学报, 2014, 63(22): 228401. doi: 10.7498/aps.63.228401
    [4] 高洪元, 李晨琬. 膜量子蜂群优化的多目标频谱分配. 物理学报, 2014, 63(12): 128802. doi: 10.7498/aps.63.128802
    [5] 张学军, 鲁友, 田峰, 孙知信, 成谢锋. 基于信任度的双门限协作频谱感知算法. 物理学报, 2014, 63(7): 078401. doi: 10.7498/aps.63.078401
    [6] 殷聪, 谭学治, 马琳, 于洋. 认知无线电中基于频谱聚合的全局比例公平调度算法. 物理学报, 2014, 63(11): 118402. doi: 10.7498/aps.63.118402
    [7] 江虹, 刘从彬, 伍春. 认知无线电网络中提高传输层端到端吞吐率的跨层参数配置. 物理学报, 2013, 62(3): 038804. doi: 10.7498/aps.62.038804
    [8] 刘允, 彭启琮, 邵怀宗, 彭启航, 王玲. 一种基于授权信道特性的认知无线电频谱检测算法. 物理学报, 2013, 62(7): 078406. doi: 10.7498/aps.62.078406
    [9] 郑仕链, 杨小牛. 用于认知无线电协作频谱感知的混合蛙跳算法群体初始化技术. 物理学报, 2013, 62(7): 078405. doi: 10.7498/aps.62.078405
    [10] 高在瑞, 沈艳霞, 纪志成. 离散时间切换广义系统的一致有限时间稳定性. 物理学报, 2012, 61(12): 120203. doi: 10.7498/aps.61.120203
    [11] 郑仕链, 杨小牛. 绿色认知无线电自适应参数调整. 物理学报, 2012, 61(14): 148402. doi: 10.7498/aps.61.148402
    [12] 徐贤胜, 郭鹏, 黄思训, 项杰. 无线电掩星滑动频谱方法和后传播方法的分析比较. 物理学报, 2011, 60(9): 099202. doi: 10.7498/aps.60.099202
    [13] 俎云霄, 周杰. 基于组合混沌遗传算法的认知无线电资源分配. 物理学报, 2011, 60(7): 079501. doi: 10.7498/aps.60.079501
    [14] 周杰, 俎云霄. 一种用于认知无线电资源分配的并行免疫遗传算法. 物理学报, 2010, 59(10): 7508-7515. doi: 10.7498/aps.59.7508
    [15] 郑仕链, 楼才义, 杨小牛. 基于改进混合蛙跳算法的认知无线电协作频谱感知. 物理学报, 2010, 59(5): 3611-3617. doi: 10.7498/aps.59.3611
    [16] 赵知劲, 徐世宇, 郑仕链, 杨小牛. 基于二进制粒子群算法的认知无线电决策引擎. 物理学报, 2009, 58(7): 5118-5125. doi: 10.7498/aps.58.5118
    [17] 赵知劲, 彭振, 郑仕链, 徐世宇, 楼才义, 杨小牛. 基于量子遗传算法的认知无线电频谱分配. 物理学报, 2009, 58(2): 1358-1363. doi: 10.7498/aps.58.1358
    [18] 赵知劲, 郑仕链, 尚俊娜, 孔宪正. 基于量子遗传算法的认知无线电决策引擎研究. 物理学报, 2007, 56(11): 6760-6766. doi: 10.7498/aps.56.6760
    [19] 王小敏, 张家树, 张文芳. 基于广义混沌映射切换的单向Hash函数构造. 物理学报, 2003, 52(11): 2737-2742. doi: 10.7498/aps.52.2737
    [20] 张家树, 肖先赐. 基于广义混沌映射切换的混沌同步保密通信. 物理学报, 2001, 50(11): 2121-2125. doi: 10.7498/aps.50.2121
计量
  • 文章访问数:  5422
  • PDF下载量:  818
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-09-24
  • 修回日期:  2014-12-08
  • 刊出日期:  2015-05-05

/

返回文章
返回