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認(rèn)知無線網(wǎng)絡(luò)中基于混合頻譜切換的最優(yōu)目標(biāo)信道選擇算法

馬彬,  包小敏,  謝顯中

馬彬, 包小敏, 謝顯中. 認(rèn)知無線網(wǎng)絡(luò)中基于混合頻譜切換的最優(yōu)目標(biāo)信道選擇算法[J]. 電子與信息學(xué)報, 2017, 39(1): 31-37. doi: 10.11999/JEIT160268
引用本文: 馬彬, 包小敏, 謝顯中. 認(rèn)知無線網(wǎng)絡(luò)中基于混合頻譜切換的最優(yōu)目標(biāo)信道選擇算法[J]. 電子與信息學(xué)報, 2017, 39(1): 31-37. doi: 10.11999/JEIT160268
MA Bin, BAO Xiaomin, XIE Xianzhong. Optimal Target Channel Selection Algorithm Based on Hybrid Spectrum Handoffs in Cognitive Radio Networks[J]. Journal of Electronics & Information Technology, 2017, 39(1): 31-37. doi: 10.11999/JEIT160268
Citation: MA Bin, BAO Xiaomin, XIE Xianzhong. Optimal Target Channel Selection Algorithm Based on Hybrid Spectrum Handoffs in Cognitive Radio Networks[J]. Journal of Electronics & Information Technology, 2017, 39(1): 31-37. doi: 10.11999/JEIT160268

認(rèn)知無線網(wǎng)絡(luò)中基于混合頻譜切換的最優(yōu)目標(biāo)信道選擇算法

doi: 10.11999/JEIT160268 cstr: 32379.14.JEIT160268
基金項目: 

國家自然科學(xué)基金(61271259, 61301123, 61471076)，重慶市基礎(chǔ)與前沿研究計劃(cstc2015jcyjA40047)，重慶郵電大學(xué)博士啟動基金(A2014-10, A2015-16)

Optimal Target Channel Selection Algorithm Based on Hybrid Spectrum Handoffs in Cognitive Radio Networks

Funds: 

The National Natural Science Foundation of China (61271259, 61301123, 61471076), The Foundation and Advanced Research Program of Chongqing (cstc2015jcyjA40047), The Doctoral Start-up Fund of Chongqing University of Posts and Telecommunications (A2014-10, A2015-16)

  • 摘要: 在主動頻譜切換中，預(yù)先確定目標(biāo)信道存在高失效風(fēng)險，從而增加切換時延的問題。該文提出一種基于混合主被動頻譜切換的最優(yōu)目標(biāo)信道選擇算法。該算法結(jié)合主動頻譜切換和被動頻譜切換的優(yōu)點(diǎn)，引入最小累積切換時延評價標(biāo)準(zhǔn)，綜合考慮次用戶的多次中斷、主用戶的到達(dá)率和非理想頻譜檢測對次用戶累積切換時延的影響，并詳細(xì)分析和推導(dǎo)了非理想檢測下次用戶的累積切換時延。仿真表明，相較于主動和被動頻譜切換中目標(biāo)信道選擇策略，在信道狀態(tài)變化頻繁或業(yè)務(wù)量較大等極端情況下，該算法的性能優(yōu)勢尤為明顯。
    Abstract: The predetermined target channel has high risk of being unavailable in the proactive-decision spectrum handoff. To solve this problem, an optimum target channel selection algorithm based on hybrid spectrum handoff is proposed. This algorithm coordinates the advantages of both the proactive-decision and reactive-decision spectrum handoffs. With the metric of minimizing the cumulative handoff delay, the impacts of secondary users multiple interruptions, primary users arrival rates and imperfect sensing on secondary users cumulative handoff delay are included and the detailed analysis and derivation of the secondary users cumulative handoff delay are conducted under imperfect sensing. Compared with proactive-decision and reactive-decision target channel selection schemes, the simulation results demonstrate that the performance of the proposed algorithm is especially excellent with frequent channel states variations or heavy traffic loads.
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  • MA Bin and XIE Xianzhong. PSHO-HF-PM: an efficient proactive spectrum handover mechanism in cognitive radio networks[J]. Wireless Personal Communications, 2014, 79(3): 1-23.
    PUSHP M and AWADHESH K S. A survey on spectrum handoff techniques in cognitive radio networks[C]. 2014 International Conference on Contemporary Computing and Informatics (IC3I), Mysore, 2014: 996-1001. doi: 10.1109/ IC3I.2014.7019755.
    WANG Chungwei and WANG Lichun. Spectrum hando for cognitive radio networks: reactive-sensing or proactive- sensing?[C]. IEEE International Performance, Computing and Communications Conference, Austin, Texas, 2008: 343-348. doi: 10.1109/PCCC.2008.4745128.
    WANG Chungwei, WANG Lichun, and CHANG Chungju. Modeling and analysis for spectrum handoffs in cognitive radio networks[J]. IEEE Transactions on Mobile Computing, 2012, 11(9): 1499-1513. doi: 10.1109/TMC.2011.155.
    ZHANG Lei, SONG Tiecheng, and WU Ming. Traffic- adaptive proactive spectrum handoff strategy for graded secondary users in cognitive radio networks[J]. Chinese Journal of Electronics, 2015, 24(4): 1-8.
    WANG Lichun and WANG Chungwei. Analysis of reactive spectrum handoff in cognitive radio networks[J]. IEEE Journal on Selected Areas in Communications, 2012, 30(10): 2016-2028. doi: 10.1109/JSAC.2012.121116.
    ZHANG Y. Spectrum handoff in cognitive radio networks: opportunistic and negotiated situations[C]. IEEE International Conference on Communications, Dresden, 2009: 1-6. doi: 10.1109/ICC.2009.5199479.
    ZHENG Shilian and YANG Xiaoniu. Target channel sequence selection scheme for proactive-decision spectrum handoff[J]. IEEE Communications Letters, 2011, 15(12): 1332-1334. doi: 10.1109/LCOMM.2011.102611.111603.
    XIAO Qinghai, LI Yunzhou, ZHAO Ming, et al. Opportunistic channel selection approach under collision probability constraint in cognitive radio systems[J]. Computer Communications, 2009, 32(18): 1914-1922.
    FATEMEH S and MASOUMEH N, Optimal probabilistic initial and target channel selection for spectrum handoff in cognitive radio networks[J]. IEEE Transactions on Wireless Communications, 2015, 14(1): 570-584. doi: 10.1109/TWC. 2014.2354407.
    WANG Lichun, WANG Chungwei, and CHANG Chungju. Optimal target channel sequence design for multiple spectrum handoffs in cognitive radio networks[J]. IEEE Transactions on Communications, 2012, 60(9): 2444-2455. doi: 10.1109/TCOMM.2012.070912.100661.
    WU Yeqing, HU Fei, SUNIL K, et al. A learning-based QoE-driven spectrum handoff scheme for multimedia transmissions over cognitive radio networks[J]. IEEE Journal on Selected Areas in Communications, 2014, 32(11): 2134-2148. doi: 10.1109/JSAC.2014.141115.
    WANG Lichun, WANG Chungwei, and ADACHI Fumiyuki. Load-balancing spectrum decision for cognitive radio networks[J]. IEEE Journal on Selected Areas in Communications, 2011, 29(4): 757-769. doi: 10.1109/JSAC. 2011.110408.
    LI Xiukui and SEYED A. Traffic pattern prediction and performance investigation for cognitive radio systems[C]. IEEE Wireless Communications and Networking Conference, Las Vegas, NV, 2008: 894-899. doi: 10.1109/WCNC.2008.163.
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出版歷程
  • 收稿日期:  2016-03-21
  • 修回日期:  2016-07-25
  • 刊出日期:  2017-01-19

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