摘要
当今的无线通信技术正朝着更高效（更高的资源效用）、更快速（更快的数据传输和处理速率）、更可靠（更强的系统可靠性）的目标发展。然而，数据处理的实时性和高速有效性，以及频谱资源的稀缺性和不可再生性，都是实现这一目标必须应对的挑战。面对这些严峻挑战，本论文研究了下一代无线通信(B3G/4G)中备受关注的两个方向：高速率、低延迟的Turbo译码，以及快速可靠的协作频谱感知，并取得了一定的研究进展，以满足下一代无线通信业务的服务质量需求。论文的主要工作概括如下：
1．在高速Turbo译码方面：针对传统高速Turbo译码中存在的缺陷，本论文分别从译码算法和译码结构两个角度进行了进一步研究。
a)对高速率、低延迟Turbo译码，进行了译码算法的改进。提出了一种新的基-4SOVA算法，并做出了完整的数学推导，该算法的关键是提出了一种新的可信度更新方法，可实现编码网格图中两步状态转移合并后的可信度更新。通过分析新算法的使用范围可知，新的基-4SOVA算法不仅适用于基于比特交织的二进制的Turbo码，同时也适用于基于比特对交织的双二进制的卷积Turbo码，而传统的基-4SOVA算法只适用于基于比特交织的二进制的Turbo码。另外，新算法的误码率性能非常接近基-4Max-Log-MAP算法，当自适应引入外信息系数后，逼近基-4MAP算法，而且新算法还具有译码延迟小、存储资源占用少等优点，达到了与计算复杂度的良好折中。
b)对高速率、低延迟Turbo译码，进行了译码结构的改进。提出了一种新的降低延迟的并行译码方案。新方案的关键是设计新型的无冲突(CF)交织器，在对CF准则分析之后，利用滑动窗的思想，提出了基于窗的CF交织器设计准则和一种实现方法，新CF交织器可以使两级SISO处理器之间传递的外信息，实时地作为彼此的先验信息用于下一次分量译码以减小译码延迟。对于相同的并行度和迭代次数，时间复杂度比较表明新并行方案的译码延迟大约下降到传统并行方案的1/4，即新并行方案大大降低了译码延迟。不过仿真结果表明新并行方案的BER性能劣于传统并行方案，并且随子块中分窗个数的增加，译码性能的下降越多。但是值得注意的是：当只将子块分成两个窗时，新并行方案的译码性能下降非常小，而且译码延迟仍大约下降到传统并行方案的1/4。针对“子块分成两个窗”这一特定情况，又进一步提出了一类改进的ISbS (M-ISbS)无冲突交织器，并为该交织器提出了一种支持可变交织长度的低复杂度实时并行实现结构，可用于子块分为两个窗的新并行译码方案。
2．在协作频谱感知方面：协作频谱感知通过利用多个用户之间的空间分集可以大大改善认知无线电系统的频谱检测性能，本论文针对不同特定场景下的认知系统，分别研究了基于最佳认知用户集和基于最佳中继的协作频谱感知方案。
a)针对相关阴影下的认知系统，研究了该场景下协作频谱感知的最佳认知用户集选择方案。首先介绍了相关对数正态阴影下协作频谱感知的假设检验模型和检测性能。然后根据虚警概率和漏检概率是否被约束，通过考虑检测性能和协作代价之间的有效折中，提出了三个最佳认知用户集选择的最优化问题。不幸的是所提最优化问题都属于NP困难问题，为了求得最佳认知用户集，进一步提出了基于自适应遗传算法(GA)的解决方法。最后，仿真结果说明，提出的认知用户集选择方案能够有效地给相关阴影下的协作频谱感知找到一个最佳的协作认知用户集。
b)针对存在多个中继的认知系统，研究了基于最佳中继的协作频谱感知方案，并重点分析了在Nakagami-m衰落信道下的检测性能。首先利用机会中继选择(ORS)技术，提出了基于机会放大转发中继的协作频谱感知(CSS-OAFR)方案，推导了该方案基于能量检测的检测性能，尤其给出了平均漏检概率紧的闭式下界，通过仿真验证了理论分析结果的有效性，并且讨论了参与选择的中继数目对检测性能影响。然后将基于部分中继选择(PRS)的AF策略应用到协作频谱感知，称为CSS-AFS-PRS方案，同样进行了类似的检测性能分析和仿真验证，此外仿真结果还表明，在CSS-AFS-PRS方案中仅两个中继参与选择就可达到相对较好的检测性能，因而可以克服选择代价。
Wireless communication today is developing towards higher resource efficiency,faster data transmission and processing speed, and better system reliability. However, inorder to achieve this goal, both the real-time and high-speed data processing and thescarcity and non-renewable nature of wireless spectrums, are the challenges that wemust face. Therefore, this work investigates the high-speed and low-delay Turbodecoding and the fast and reliable cooperative spectrum sensing (CSS) for nextgeneration wireless communications (B3G/4G), and obtains certain research progress tosatisfy the requirements of quality of service (QoS) for B3G/4G services. The maincontribution of this work can be summarized as follows:
1. High speed Turbo decoding issues: Aiming at the defects of the conventionalhigh-speed Turbo decoding, further studies are made from two aspects, i.e., thedecoding algorithm and the decoding structure, respectively.
a) Decoding algorithms are improved for high-speed and low-delay Turbodecoding. A novel radix-4SOVA algorithm is proposed and its complete mathematicalderivation is given. The key of the algorithm is to propose a novel reliability updatemethod which achieves the reliability update after combining two-step state transitionsin trellis diagram. By analyzing the range of application of the proposed algorithm, it isobtained that the algorithm is not only suitable for binary Turbo codes based on bitinterleaving, but also doubinary convolutional Turbo codes based on double-bitinterleaving. But the conventional radix-4SOVA algorithm is only suitable for binaryTurbo codes based on bit interleaving. In addition, simulation results show that the BERperformance of the novel algorithm is very close to that of radix-4Max-Log-MAP, andapproaches radix-4MAP when the extrinsic information coefficient is adaptively added.Moreover, it still has other virtues such as low decoding delay and small storageresource requirements, and achieves a good tradeoff with the computational complexity.
b) Decoding structures are improved for high-speed and low-delay Turbo decoding.A novel parallel decoding scheme is proposed to decrease the decoding delay. The keyof the novel scheme is to design a novel collision-free (CF) interleaver. After theanalysis of the CF criterion, the design criterion and an implementation approach of theCF interleaver based on the window are proposed by using the idea of the slidingwindow. The novel CF interleaver allows extrinsic information immediately as eachother’s priori information to start the next component decoding so as to decreasedecoding delay. Under the condition of the same degree of parallelism and number of iterations, the comparison of time complexity shows that the decoding delay of thenovel parallel scheme is only about a quarter of that required for the conventionalparallel scheme, i.e., the novel scheme greatly decreases the decoding delay.Unfortunately, simulation results show that the novel parallel scheme suffers from theBER performance degradation compared with the conventional parallel scheme, andwith the increase in the number of dividing a subblock into windows, the performancedegrades more and more seriously. However, note that when a subblock only dividesinto two windows, the BER performance degradation of the novel parallel scheme isvery small, and its decoding delay is still about a quarter of that required for theconventional parallel scheme. Aiming at the particular case that a subblock divides intotwo windows, modified inter-subblock shuffle (M-ISbS) CF interleavers are furtherproposed, and its low-complexity architecture design for parallel Turbo decoding is alsogiven which can realize parallel outputs of the on-line interleaving addresses andsupport variable interleaving lengths. Therefore, the M-ISbS interleavers can be appliedto the novel parallel scheme where a subblock divides into two windows.
2. Cooperative spectrum sensing issues: The CSS has been shown to be aneffective approach to improve the detection performance by exploiting the spatialdiversity among multiple users. Aiming at the cognitive systems of different particularscenarios, CSS schemes based on the optimal cognitive user set and the best relay areinvestigated respectively.
a) Aiming at the cognitive system under correlated shadowing, the optimalselection scheme of cognitive user set is studied for CSS. First, the hypothesis testingmodel and the detection performance of CSS under the correlated log-normalshadowing scenario are introduced. Afterwards, based on whether the false-alarm andmissed-detection probabilities are constrained, three optimization problems areformulated to find the optimal set of cognitive users participating in cooperation, whichtake into account the tradeoff between detection performance and cooperation overhead.Nevertheless, it is very hard to obtain optimal solutions for them directly, known asnondeterministic polynomial (NP)-hard problems. Then the solutions using adaptivegenetic algorithms are presented, which are known as stochastic search techniquesbased on the mechanism of natural selection and natural genetics, and have successfullybeen applied to many complex optimization problems in wireless communications.Finally, a series of experiments are carried out and the results are analyzed,demonstrating that the proposed schemes can optimally select a set of cognitive users toparticipate in cooperation under the correlated shadowing scenario.
b) Aiming at the cognitive system with multiple relays, the CSS schemes based onthe best relay are studied, and their detection performance over Nakagami-m fadingchannels is especially focused. First, the CSS scheme based on opportunisticamplify-and-forward relaying (denoted by CSS-OAFR scheme) is presented by usingopportunistic relay selection. The detection performance using the energy detector isderived for the CSS-OAFR scheme, and especially a tight closed-form lower bound ofthe average missed-detection probability is proposed for the convenience ofperformance evaluation in practice. By simulations, the theoretical analysis results arevalidated, and the influence of the number of relays on the detection performance is alsodiscussed. Second, the CSS scheme using the AF strategy with partial relay selection(denoted by CSS-AFS-PRS scheme) is investigated. The similar detection performanceanalysis and simulation validation are also provided for the CSS-AFS-PRS scheme. Inparticular, simulation results also show that in the CSS-AFS-PRS scheme the use ofonly two relays is enough to achieve relatively good detection performance, meaningthat the selection overhead of systems is overcome.
引文
[1]李建东,杨家玮,个人通信.北京:人民邮电出版社,1998.
[2]杨家玮,盛敏,刘勤,移动通信基础(第二版).北京:电子工业出版社,2008.
[3]赵林靖, OFDM及OFDMA同步技术研究.西安电子科技大学博士论文,2008.
[4]李钊, MIMO无线通信自适应技术研究.西安电子科技大学博士论文,2009.
[5] J. Chuang and N. Sollenberger,“Beyond3G: Wideband wireless data accessbased on OFDM and dynamic packet assignment,” IEEE Commun. Mag., vol.38,no.7, pp.78-87, Jul.2000.
[6] R. Berezdivin, R. Bremig, and R. Topp,“Next-generation wirelesscommunications concepts and technologies,” IEEE Commun. Mag., vol.40, no.3,pp.108-116, Mar.2002.
[7]3GPP TD RP-080137,“Proposed SID on LTE-Advanced”.
[8]何琳琳,杨大成,“4G移动通信系统的主要特点和关键技术,”移动通信, no.10, pp.34-36,2004.
[9] M. Steer,“Beyond3G,” IEEE Mircrow. Mag., vol.8, no.1, pp.76-82, Feb.2007.
[10] A. J. Goldsmith and S. G. Chua,“Variable-rate variable-power MQAM for fadingchannels,” IEEE Trans. Commun., vol.45, no.10, pp.1218-1230, Oct.1997.
[11] C. Berrou, A. Glavieux, and P. Thitimajshima,“Near Shannon limiterror-correcting coding and decoding: Turbo-codes(1),” in Proc. IEEEInternational Conference on Communications, May1993, pp.1064-1070.
[12] R. G. Gallager,“Low-density parity-check code,” IRE Trans. Inform. Theory, vol.8, no.1, pp.21-28, Jan.1962.
[13] J. Mitola,“The software radio architecture,” IEEE Communications Magazine,vol.33, no.5, pp.26-38, May1995.
[14] J. Mitola and G. Q. Maguire,“Cognitive radios: Making software radios morepersonal,” IEEE Pers. Commun., vol.6, no.4, pp.13-18, Aug.1999.
[15] J. Mitola, Cognitive radio: An integrated agent architecture for software definedradio. PhD thesis, Royal Inst. Technol.(KTH), Stockholm, Sweden,2000.
[16] A. Sendonaris, E. Erkip, and B. Aazhang,“Increasing uplink capacity via usercooperation diversity,” in Proc. IEEE Int. Symp. Information Theory (ISIT), Aug.1998, p.156.
[17] A. Sendonaris, E. Erkip, and B. Aazhang,“User cooperation diversity-Part I:system description,” IEEE Trans. Commun., vol.51, no.11, pp.1927-1938, Nov.2003.
[18] A. Sendonaris, E. Erkip, and B. Aazhang,“User cooperation diversity-Part II:implementation aspects and performance analysis,” IEEE Trans. Commun., vol.51, no.11, pp.1939-1948, Nov.2003.
[19] W. P. Siriwongpairat, T. Himsoon, W. F. Su, and J. K. R. Liu,“Optimumthreshold-selection relaying for decode-and-forward cooperation protocol,” inProc. IEEE Wireless Communications and Networking Conference, Apr.2006, pp.1015-1020.
[20] J. A. C. Bingham,“Multicarrier modulation for data transmission: an idea whosetime has come,” IEEE Commun. Mag., vol.28, no.5, pp.5-14, May1990.
[21] J. Chuang, and N. Sollenberger,“Beyond3G: Wideband wireless data accessbased on OFDM and dynamic packet assignment,” IEEE Commun. Mag., vol.38,no.7, pp.78-87, Jul.2000.
[22]尹长川,罗涛,乐光新,多载波宽带无线通信技术(第一版).北京:北京邮电大学出版社,2004.
[23] G. J. Foschini,“Layered space-time architecture for wireless communication in afading environment when using multi-element antennas,” Bell Labs TechnicalJournal, vol.1, no.2, pp.41-59,1996.
[24] E. Biglieri, R. Calderbank, A. Constantinides, A. Goldsmith, A. Paulraj, and H. V.Poor, MIMO Wireless Communications. Cambridge, UK: Cambridge UniversityPress,2007.
[25] A. B. Gershman and N. D. Sidiropoulos, Space-Time Processing for MIMOCommunications. UK: John Wiley&Sons, Ltd,2005.
[26] A. Alexiou and M. Haardt,“Smart antenna technologies for future wirelesssystems: trends and challenges,” IEEE Commun. Mag., vol.42, no.9, pp.90-97,Sept.2004.
[27] Y. S. Song, H. M. Kwon, and B. J. Min,“Smart antennas for3G andfuture-generation code division multiple access wireless communications,” inProc. IEEE Int. Conf. on Phased Array Syst. and Technol., May2000, pp.69-72.
[28] A. Giulietti, L. Perre, and A. Strum,“Parallel turbo coding interleavers: avoidingcollisions in accesses to storage elements,” Electronics Letters, vol.38, no.5, pp.232-234, Feb.2002.
[29] Z. Wang and K. K. Parhi,“High performance, high throughput Turbo/SOVAdecoder design,” IEEE Trans. Commun., vol.51, no.4, pp.570-579, Apr.2003.
[30] S. G. Lee, C. H. Wang, and W. H. Sheen,“Architecture design of QPP interleaverfor parallel turbo decoding,” in Proc. IEEE71st vehicular technology conference,May2010, pp.1-5.
[31]任德锋,葛建华,宫丰奎,王勇,“新颖的低延迟并行Turbo译码方案,”通信学报, vol.32, no.6, pp.37-44, Jun.2011.
[32]任德锋,葛建华,王勇,宋英杰,“一种新的基-4SOVA译码算法,”电子与信息学报, vol.33, no.8, pp.1963-1968, Aug.2011.
[33] D. F. Ren, J. H. Ge, and J. Li,“Modified collision-free interleavers for high speedTurbo decoding,” Wireless Personal Communications, vol.68, no.3, pp.939-948,Feb.2013.
[34] S. M. Mishra, A. Sahai, and R. W. Brodersen,“Cooperative sensing amongcognitive radios,” in Proc. IEEE Int. Conf. Communications, Istanbul, Turkey,Jun.2006, pp.1658-1663.
[35] A. Ghasemi and E. S. Sousa,“Opportunistic spectrum access in fading channelsthrough collaborative sensing,” J. of Commun., vol.2, no.2, pp.71-82, Mar.2007.
[36] H. Rifa-Pous, M. J. Blasco, and C. Garrigues,“Review of robust cooperativespectrum sensing techniques for cognitive radio networks,” Wireless personalCommunications, vol.67, no.2, pp.175-198, Nov.2012.
[37] Y. Jiang, J. Tian, H. Chen, and H. Hu,“Cyclostationarity-based decisionreporting scheme for cooperative spectrum sensing,” Wireless personalCommunications, vol.68, no.3, pp.697-710, Feb.2013.
[38] D. F. Ren, J. H. Ge, and J. Li,“Secondary user selection scheme using adaptivegenetic algorithms for cooperative spectrum sensing under correlatedshadowing,” Wireless Personal Communications, pp.1-20, Published online:18Sept.,2012.
[39] J. G. Proakis, Digital Communications.5th Ed. New York: McGraw-Hill,1999.
[40] J. Hagenauer, E. Offer, and L. Papke,“Iterative decoding of binary block andconvolutional codes,” IEEE Trans. Inform. Theory, vol.42, no.2, pp.429-445,Mar.1996.
[41] S. Benedetto and G. Montorsi,“Unveiling turbo codes: Some results on parallelconcatenated coding schemes,” IEEE Trans. Inform. Theory, vol.42, no.2, pp.409-428, Mar.1996.
[42] S. Benedetto and G. Montorsi,“Design of parallel concatenated convolutionalcodes,” IEEE Trans. Commun., vol.44, no.5, pp.591-600, May1996.
[43] D. Divsalar, S. Dolinar, R. J. McEliece, and F. Pollara,“Transfer function boundson the performance of turbo codes,” JPL TDA Progress Report42-122, pp.44-55,Aug.1995.
[44] T. M. Duman and M. Salehi,“New performance bounds for turbo codes,” IEEETrans. Commun., vol.46, no.6, pp.717-723, Jun.1998.
[45] T. M. Duman, Turbo codes and turbo coded modulation systems: analysis andperformance bounds. Doctor Thesis of Northeastern University, Boston,Massachusetts, May1998.
[46] I. Sason and S. Shamai,“Improved upper bounds on the ML decoding errorprobability of parallel and serial concatenated turbo codes via their ensembledistance spectrum,” IEEE Trans. Inform. Theory, vol.46, no.1, pp.24-47, Jan.2000.
[47] D. Divsalar,“A simple tight bound on error probability of block codes withapplication to turbo codes,” TMO Progress Report,42-139, pp.1-35, Nov.1999.
[48] R. Herzog and C. Weiβ,“Improved tight performance bounds on concatenatedcodes,” in Proc. Globecom’99, Dec.1999, pp.2427-2431.
[49] D. Divsalar and R. J. McEliece,“Effective free distance of turbo codes,” Electron.Lett., vol.32, no.5, pp.445-446, Feb.1996.
[50] L. C. Perez, J. Seghers, and D. J. Costello,“A distance spectrum interpretation ofturbo codes,” IEEE Trans. Inform. Theory, vol.42, no.6, pp.1698-1709, Nov.1996.
[51] G. Battail,“A conceptual framework for understanding turbo codes,” IEEE J.Select. Areas Connnun., vol.16, no.2, pp.245-254, Feb.1998.
[52] S. Benedetto and G. Montorsi,“Role of recursive convolutional codes in turbocodes,” Electron. Lett., vol.31, no.11, pp.858-859, May1995.
[53]吴伟陵,“通向信道编码定理的Turbo码及其性能分析,”电子学报, vol.26, no.7, pp.36-40,1998.
[54]叶中行, V. Wei,“Turbo码的若干新进展,”电子学报, vol.26, no.7, pp.41-46,1998.
[55] P. Robertson and T. Worz,“Coded modulation scheme employing turbo codes,”Electron. Lett., vol.31, no.18, pp.1546-1547, Aug.1995.
[56] P. Robertson and T. Worz,“A novel bandwidth efficient coding schemeemploying turbo codes,” in Proc. IEEE International Conference onCommunications, Jun.1996, pp.962-967.
[57] P. Robertson and T. Worz,“Bandwidth-efficient turbo trellis-coded modulationusing punctured component codes,” IEEE J. Select Areas Commun, vol.16, no.2,pp.206-218, Feb.1998.
[58] D. Divsalar and F. Pollara,“Turbo trellis coded modulation with iterativedecoding for mobile satellite communications,” JPL TDA Progress Report,1997.
[59] L. U. Wachsman and J. Huber,“Power and bandwidth efficient digitalcommunication using turbo codes in multilevel codes,” Europ Trans.Telecommun., vol.6, no.5, pp.557-567, Sept.1995.
[60] K. Fazel and L. Papke,“Combined multilevel turbo-code with8PSKmodulation,” in Proc. Globecom’95, Nov.1995, pp.649-653.
[61] H. Herzberg,“Multilevel turbo coding with short interleavers,” IEEE J. SelectAreas Commun., vol.16, no.2, pp.303-309, Feb.1998.
[62] L. U. Wachsman, R. F. H. Fischer, and J. B. Huber,“Multilevel codes:Theoretical concepts and practical design rules,” IEEE Trans. Inform. Theory, vol.45, no.5, pp.1361-1391, Jul.1999.
[63] M. J. Gertsman and J. H. Lodge,“Symbol-by-symbol MAP demodulation ofCPM and PSK signals on Rayleigh flat-fading channels,” IEEE Trans. Commun.,vol.45, no.7, pp.788-799, Jul.1997.
[64] P. Hoeher and J. Lodge,“Turbo DPSK: Iterative differential PSK demodulationand channel decodings,” IEEE Trans. Commun., vol.47, no.6, pp.837-843, Jun.1999.
[65] U. Hansson,“Soft information transfer for sequence detection with concatenatedreceiver,” IEEE Trans. Commun., vol.44, no.9, pp.1086-1095, Sep.1998.
[66] M. Tuchler, R. Koetter, and A. Singer,“Turbo equalization: Principles and newresults,” IEEE Transactions on Communications, vol.50, no.5, pp.754-767, May2002.
[67] M. Moher,“An iterative multiuser decoder for near-capacity communications,”IEEE Trans. Commun., vol.46, no.7, pp.870-880, Jul.1998.
[68] M. C. Reed, C. B. Schlegel, P. D. Alexander, and J. A. Asenstorfer,“Iterativemultiuser detection for CDMA with FEC: Near-single-user performance,” IEEETrans. Commun., vol.46, no.12, pp.1693-1699, Dec.1998.
[69] S. Kaifan and J. Hagenauer,“Multi-carrier CDMA with iterative decoding andsoft-interference cancellation,” in Proc. Globecom’97, Nov.1997, pp.6-10.
[70] X. Wang and H. V. Poor,“Iterative(Turbo) soft interference cancellation anddecoding for coded CDMA,” IEEE Trans. Commun., vol.47, no.7, pp.1046-1061, Jul.1999.
[71] B. Zhao and M. C. Valenti,“Distributed turbo coded diversity for relay channel,”Electron. Lett., vol.39, no.10, pp.786-787, May2003.
[72] M. C. Valenti and B. Zhao,“Distributed turbo codes: towards the capacity of therelay channel,” in Proc. IEEE58th Vehicular Technology Conference, Oct.2003,pp.322-326.
[73] Y. Li, B. Vucetic, T. F. Wong, and M. Dohler,“Distributed turbo coding with softinformation relaying in multihop relay networks,” IEEE J. Sel. Areas Commun.,vol.24, no.11, pp.2040-2050, Nov.2006.
[74] J. Chen and A. Abedi,“Distributed turbo coding and decoding for wireless sensornetworks,” IEEE Communications Letters, vol.15, no.2, pp.166-168, Feb.2011.
[75] D. F. Ren, J. H. Ge, and X. Y. Shi,“Novel Distributed Turbo Coding Scheme inTwo-Hop Relay Networks,” in Proc. IEEE20124th International Conference onIntelligent Networking and Collaborative Systems, Sept.2012, pp.546-549.
[76] Federal Communications Commission, Notice of proposed rulemaking, in thematter of unlicensed operation in the TV broadcast bands (ET Docket No.04-186)and additional spectrum for unlicensed devices below900MHz and in the3GHzband (ET Docket No.02-380). FCC04-113, May2004.
[77]郭阳,王衍文,“认知无线电技术及其政策影响和市场前景预测,”中兴通讯技术, vol.13, no.3, pp.27-30,2007.
[78] IEEE802.22, Working Group on Wireless Regional Area Networks (WRAN):Enabling Rural Broadband and Wireless Access Using Cognitive RadioTechnology in TV Whitespaces, http://grouper.ieee.org/groups/802/22/.
[79]郭彩丽,冯春燕,曾志民,认知无线电网络技术及应用.北京：电子工业出版社,2010.
[80] H. Urkowitz,“Energy detection of unknown deterministic signals,” Proceedingsof the IEEE, vol.55, no.4, pp.523-531, Apr.1967.
[81] H. Tang,“Some physical layer issues of wide-band cognitive radio systems,” inProc. IEEE Symp. New Frontiers in Dynamic Spectrum AccessNetworks(DySPAN), Nov.2005, pp.151-159.
[82] D. Cabric, A. Tkachenko, and R. W. Brodersen,“Experimental study of spectrumsensing based on energy detection and network cooperation,” in Proc. ACM Int.Workshop on Technology and Policy for Accessing Spectrum, Aug.2006.
[83] A. Leu, K. Steadman, M. McHenry, and J. Bates,“Ultra sensitive TV detectormeasurements,” in Proc. IEEE DySPAN, Nov.2005, pp.30-36.
[84] D. Slepian,“Some comments on the detection of gaussian signals in Gaussiannoise,” IRE Transactions on Information Theory, vol.4, no.2, pp.65-68, Jun.1958.
[85] A. Sahai, N. Hoven, and R. Tandra,“Some fundamental limits on cognitiveradio,” in Proc. Forty-second Allerton Conference on Communication, Control,and Computing,2004.
[86] D. Cabric, A. Tkachenko, and R. Brodersen,“Spectrum sensing measurements ofpilot, energy, and collaborative detection,” in Proc. Military CommunicationsConference, Oct.2006, pp.1-7.
[87] R. Tandra and A. Sahai,“Fundamental limits on detection in low SNR undernoise uncertainty,” in Proc. IEEE Int. Conf. Wireless Networks, Commun. andMobile Computing, Jun.2005, pp.464-469.
[88] R. Tandra and A. Sahai,“SNR walls for signal detection,” IEEE Journal ofSelected Topics in Signal Processing, vol.2, no.1, pp.4-17, Feb.2008.
[89] IEEE802.22Working group,“Spectrum sensing requirements summary,” DocNum.22-06-0089-04-0000. Jul.2006. http://www.ieee802.org/22/Meetingdocuments/2006July/22-06-0089-04-0000-Spectrum-Sensing-Requirements-Summary.doc.
[90] Y. H. Zeng and Y.-C. Liang,“Covariance Based Signal Detections for CognitiveRadio,” in Proc. IEEE DySPAN, Apr.2007, pp.202-207.
[91] P. Sutton, K. Nolan, and L. Doyle,“Cyclostationary signatures in practicalcognitive radio applications,” IEEE Journal on Selected Areas in Commun., vol.26, no.1, pp.13-24, Jan.2008.
[92] S. Haykin, D. J. Thomson, and J. H. Reed,“Spectrum sensing for cognitiveradio,” Proceedings of the IEEE, vol.97, no.5, pp.849-877, May2009.
[93] K. Kim, I. A. Akbar, K. K. Bae, J.-S. Um, C. M. Spooner, and J. H. Reed,“Cyclostationary approaches to signal detection and classification in cognitiveradio,” in Proc. IEEE DySPAN, Apr.2007, pp.212-215.
[94] W. M. Gardner and C. M. Spooner,“Signal interception: performance advantagesof cycle-feature detectors,” IEEE Trans. Commun., vol.40, no.1, pp.149-159,Jan.1992.
[95] D. Cabric and R. Brodersen,“Physical layer design issues unique to cognitiveradio systems,” in Proc. IEEE Int. Symposium on Personal, Indoor and MobileRadio Commun., Sept.2005, pp.759-763.
[96] L. P. Goh, Z. Lei, and F. Chin,“DVB detector for cognitive radio,” in Proc. IEEEICC, Jun.2007, pp.6460-6465.
[97] S. Haykin,“Cognitive radio: Brain-empowered wireless communications,” IEEEJ. Sel. Areas Commun., vol.23, no.2, pp.201–220, Feb.2005.
[98] Z. Tian and G. B. Giannakis,“A wavelet approach to wideband spectrum sensingfor cognitive radios,” in Proc. IEEE Int. Conf. Cognitive Radio Oriented WirelessNetworks and Communications, Jun.2006, pp.1-5.
[99] Z. Tian and G. B. Giannakis,“Compressed sensing for wideband cognitiveradios,” in Proc. ICASSP, Apr.2007, pp.15-20.
[100] K. Challapali, S. Mangold, and Z. Zhong,“Spectrum agile radio: Detectingspectrum opportunities,” in Proc. Int. Symposium on Advanced RadioTechnologies, Mar.2004, pp.1-3.
[101] A. Ghasemi and E. Sousa,“Collaborative Spectrum Sensing for OpportunisticAccess in Fading Environments,” in Proc. IEEE DySPAN, Nov.2005, pp.131-136.
[102] C. H. Sun, W. Zhang, and K. B. Letaief,“Cluster-Based Cooperative SpectrumSensing in Cognitive Radio Systems,” in Proc. IEEE Int. Conf. Communications,Jun.2007, pp.2511-2515.
[103] E. Visotsky, S. Kuffner, and R. Peterson,“On collaborative detection of TVtransmissions in support of dynamic spectrum sharing,” in Proc.1st IEEEInternational Symposium on New Frontiers in Dynamic Spectrum AccessNetworks, Nov.2005, pp.338-345.
[104] Z. Quan, S. Cui, and A. H. Sayed,“Optimal Linear Cooperation for SpectrumSensing in Cognitive Radio Networks,” IEEE J. Select. Topics Signal. Process.,vol.2, no.1, pp.28-40, Feb.2008.
[105] G. Ganesan and Y. Li,“Cooperative spectrum sensing in cognitive radio, Part I:two user networks,” IEEE Trans. Wireless Commun., vol.6, no.6, pp.2204-2213,Jun.2007.
[106] G. Ganesan and Y. Li,“Cooperative spectrum sensing in cognitive radio, Part II:multiuser networks,” IEEE Trans. Wireless Commun., vol.6, no.6, pp.2214-2222, Jun.2007.
[107] S. Atapattu, C. Tellambura, and H. Jiang,“Relay based cooperative spectrumsensing in cognitive radio networks,” in Proc. IEEE GLOBECOM, Nov.2009, pp.1-5.
[108] Q. Chen, M. Motani, and W.-C. Wong,“Cooperative spectrum sensing strategieswith multiple relays,” in Proc. IEEE ICCS, Nov.2010, pp.540-544.
[109] D.-G. Choi, I.-G. Lee, and J.-W. Jung,“High-speed Turbo decoding algorithmand ite implementation,” in Proc. IEEE ICCS, Sept.2004, pp.466-470.
[110] C.-H. Tang, C.-C. Wong, C.-L. Chen, C.-C. Lin, and H.-C. Chang,“A952MS/sMax-Log MAP decoder chip using radix-4×4ACS architecture,” in Proc. IEEEASSCC, Nov.2006, pp.79-82.
[111] C. Zhang, X. J. Wang, F. Ye, and J. Y. Ren,“A400Mb/s radix-4MAP decoderwith fast recursion architecture,” in Proc. ICACT, Feb.2008, pp.1339-1342.
[112] H.-T. Chuang, K.-H. Tseng, and W.-C. Fang,“A high-throughput Radix-4Log-MAP decoder with low complexity LLR architecture,” in Proc. IEEEVLSI-DAT, Apr.2009, pp.231-234.
[113] C.-H. Lin, C.-Y. Chen, T.-H. Tsai, and A.-Y. Wu,“Low-power memory-reducedtraceback MAP decoding for double-binary convolutional Turbo decoder,” IEEETransactions on Circuits and Systems I: Regular Papers, vol.56, no.5, pp.1005-1016, May2009.
[114] E. Luthi and E. Casseau,“High rate soft output Viterbi decoder,” in Proc.European Design and Test Conference, Mar.1996, pp.313-319.
[115] E. F. Haratsch and K. K. Fitzpatrick,“A Radix-4soft-output viterbi architecture,”in Proc. IEEE VLSI-DAT, Apr.2008, pp.224-227.
[116] J.-M. Hsu and C.-L. Wang,“A parallel decoding scheme for turbo codes,” inProc. IEEE ISCAS, Jun.1998, pp.445-448.
[117] S. Yoon and Y. Bar-Ness,“A parallel MAP algorithm for low latency turbodecoding,” IEEE Communications Letters, vol.6, no.7, pp.288-290, Jul.2002.
[118] S. M. Karim and I. Chakrabarti,“An improved low-power high-throughputlog-MAP turbo decoder,” IEEE Transactions on Consumer Electronics, vol.56,no.2, pp.450-457, May2010.
[119] M. Marandian, J. Fridman, Z. Zvonar, and M. Salehi,“Performance analysis ofturbo decoder for3GPP standard using the sliding window algorithm,” in Proc.IEEE PIMRC, Sept.2001, pp.127-131.
[120] C.-M. Wu, M.-D. Shieh, C.-H. Wu, Y.-T. Hwang, and J.-H. Chen,“VLSIarchitectural design tradeoffs for sliding-window Log-MAP decoders,” IEEETransactions on Very Large Scale Integration(VLSI) Systems, vol.13, no.4, pp.439-447, Apr.2005.
[121] Y. Zhang, VLSI Architectures for Turbo Code Decoders, LDPC code Decodersand List Sphere Decoders. in partial fulfillment of the requirements for the degreeof doctor of philosophy, May2007.
[122] A. Nimbalker, T. E. Fuja, D. J. Costello, T. K. Blankenship, and B. Classon,“Contention-free interleavers,” in Proc. IEEE ISIT, Jul.2004, p.54.
[123] A. Nimbalker, T. K. Blankenship, B. Classon, T. E. Fuja, and D. J. Costello,“Contention-free interleavers for high-throughput turbo decoding,” IEEETransactions on Communications, vol.56, no.8, pp.1258-1267,2008.
[124] C. Berrou, P. Adde, E. Angui, and S. Faudeil,“A low complexity soft-outputviterbi decoder architecture,” in Proc. IEEE International Conference onCommunications, May1993, pp.737-740.
[125] A. Bletsas, A. Khisti, D. P. Reed, and A. Lippman,“A simple cooperativediversity method based on network path selection,” IEEE J. Select. AreasCommun., vol.24, no.3, pp.659-672, Mar.2006.
[126] A. Bletsas, H. Shin, and M. Z. Win,“Outage optimality of opportunisticamplify-and-forward relaying,” IEEE Commun. Lett., vol.11, no.3, pp.261-263,Mar.2007.
[127] A. Bletsas, H. Shin, and M. Z. Win,“Outage analysis for cooperativecommunication with multiple amplify-and-forward relays,” Electron. Lett., vol.43, no.6, pp.51-52, Mar.2007.
[128] A. Bletsas, H. Shin, and M. Z. Win,“Cooperative communications withoutage-optimal opportunistic relaying,” IEEE Trans. Wireless Commun., vol.6,no.9, pp.3450-3460, Sep.2007.
[129] Y. Zhao, R. Adve, and T. J. Lim,“Symbol error rate of selection amplify-and-forward relay systems,” IEEE Commun. Lett., vol.10, no.11, pp.757-759, Nov.2006.
[130] Y. Zhao, R. Adve, and T. J. Lim,“Improving amplify-and-forward relaynetworks: optimal power allocation versus selection,” IEEE Trans. WirelessCommun., vol.6, no.8, pp.3114-3123, Aug.2007.
[131] P. Jung,“Comparison of turbo-code decoders applied to short frame transmissionsystems,” IEEE J. Select. Areas Commun., vol.14, no.3, pp.530-537, Apr.1996.
[132] L. Lin and R. S. Cheng,“Improvements in SOVA-based decoding for turbocodes,” in Proc. IEEE ICC, Jun.1997, pp.1473-1478.
[133] J. Tan and G. L. Stuber,“Soft Output Viterbi Algorithm(SOVA) for non-binaryTurbo codes,” in Proc. IEEE International Symposium on Information Theory,Jun.2000, p.483.
[134] J. J. Liu and G. F. Tu,“Iterative decoding of non-binary Turbo codes usingsymbol based SOVA algorithm,” in Proc. IEEE International Conference onCommunications, Circuits and Systems, Jun.2006, pp.689-693.
[135] L.-H. Ang, W.-G. Lim, and M. Kamuf,“Modification of SOVA-based algorithmsfor efficient hardware implementation,” in Proc. IEEE71st Vehicular TechnologyConference, May2010, pp.1-5.
[136]张成,苏文艳,刘亮,叶凡,任俊彦,“具有高速递归结构的基-4MAP译码器,”计算机工程与应用, vol.45, no.3, pp.77-80,2009.
[137]3GPP,3GPP TS36.212v8.7.03rd generation partnership project; technicalspecification group radio access network; evolved universal terrestrial radioaccess; multiplexing and channel coding (Release8).3rd Generation PartnershipProject, Technical Report, May2009.
[138] S.-J. Lee, N. R. Shanbhag, and A. C. Singer,“Area efficient high-throughputMAP decoder architectures,” IEEE Transactions on VLSI Systems, vol.13, no.8,pp.921-933, Aug.2005.
[139] I. A. Al-Mohandes and M. I. Elmasry,“Low-energy design of a3G-compliantturbo decoder,” in Proc. IEEE NEWCAS, Jun.2004, pp.153-156.
[140] S. Crozier and P. Guinand,“High-performance low-memory interleaver banks forturbo-codes,” in Proc. IEEE vehicular technology conference, Oct.2001, pp.2394-2398.
[141] A. Tarable, S. Benedetto, and G. Montorsi,“Mapping interleaving laws to parallelturbo and LDPC decoder architectures,” IEEE Transactions on InformationTheory, vol.50. no.9, pp.2002-2009, Sept.2004.
[142] R. Y. Shao, S. Lin, and M. P. C. Fossorier,“Two simple stopping criteria forturbo decoding,” IEEE Transactions on Communications, vol.47, no.8, pp.1117-1120, Aug.1999.
[143] Federal Communications Commission, Spectrum policy task force report, FCC02-155. Nov.2002.
[144] R. W. Broderson, A. Wolisz, D. Cabric, S. M. Mishra, and D. Willkomm,“CORVUS: A Cognitive Radio Approach for Usage of Virtual UnlicensedSpectrum,” Berkeley, CA: Univ. California Berkeley Whitepaper, Jul.2004.
[145] T. Erpek, M. Lofquist, and K. Patton,“Spectrum occupancy measurements:Loring Commerce Centre, Limestone, ME, Sep.18-20,2007,” Shared SpectrumCo., Vienna, VA,2007.
[146] I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty,“Nextgeneration/dynamic spectrum access/cognitive radio wireless networks: Asurvey,” Comput. Netw., vol.50, no.13, pp.2127-2159, Sep.2006.
[147] A. Ghasemi and E. S. Sousa,“Asymptotic performance of collaborative spectrumsensing under correlated log-normal shadowing,” IEEE Commun. Lett., vol.11,no.1, pp.34-36, Jan.2007.
[148] Y. Chen,“Optimum number of secondary users in collaborative spectrum sensingconsidering resources usage efficiency,” IEEE Commun. Lett., vol.12, no.12, pp.877-879, Dec.2008.
[149] S. Xie, Y. Liu, Y. Zhang, and R. Yu,“A parallel cooperative spectrum sensing incognitive radio networks,” IEEE Trans. Veh. Technol., vol.59, no.8, pp.4079-4092, Oct.2010.
[150] M. Matsui, H. Shiba, K. Akabane, and K. Uehara,“A novel cooperative sensingtechnique for cognitive radio,” in Proc.18th Annual IEEE InternationalSymposium on Personal, Indoor and Mobile Radio Communications, Sept.2007,pp.1-5.
[151] N. Pratas, N. Marchetti, N. R. Prasad, A. Rodrigues, and R. Prasad,“Adaptivecounting rule for cooperative spectrum sensing under correlated environments,”Wireless personal Communications, vol.64, no.1, pp.93-106, May2012.
[152] M. Srinivas and L. M. Patnaik,“Adaptive probabilities of crossover and mutationin Genetic Algorithms,” IEEE Transactions on systems, man and cybernetics, vol.24, no.4, pp.656-667, Apr.1994.
[153] L. M. O. Khanbary and D. P. Vidyarthi,“Reliability-based channel allocationusing genetic algorithm in mobile computing,” IEEE Trans. Veh. Technol., vol.58, no.8, pp.4248-4256, Oct.2009.
[154] Z. Michalewicz, Genetic Algorithm+Data Structures=Evolution Programs.Berlin, Germany: Springer-Verlag,1996.
[155] M. A. C. Lima, A. F. R. Araujo, and A. C. Cesar,“Adaptive genetic algorithmsfor dynamic channel assignment in mobile cellular communication systems,”IEEE Trans. Veh. Technol., vol.56, no.5, pp.2685-2696, Sept.2007.
[156] M. Gudmundson,“Correlation model for shadow fading in mobile radiosystems,” Electron. Lett., vol.27, no.23, pp.2145-2146, Nov.1991.
[157] H. P. Yuen, R. S. Kennedy, and M. Lax,“Optimum testing of multiplehypotheses in quantum detection theory,” IEEE Trans. Inform. Theory, vol. IT-21,No.2, pp.125-134, Mar.1975.
[158] F. Benedetto, G. Giunta, and A. Neri,“A Bayesian business model for video-callbilling for end-to-end QoS provision,” IEEE Trans. Veh. Technol., vol.58, no.2,pp.836-842, Feb.2009.
[159] S. S. M. Patra, K. Roy, S. Banerjee, and D. P. Vidyarthi,“Improved geneticalgorithm for channel allocation with channel borrowing in mobile computing,”IEEE Trans. Mobile Comput., vol.5, no.7, pp.884-892, Jul.2006.
[160] N. Sharma and K. R. Anupama,“A novel genetic algorithm for adaptive resourceallocation in MIMO-OFDM systems with proportional rate constraint,” WirelessPersonal Communications, vol.61, no.1, pp.113-128, Nov.2011.
[161] S. H. Liao, C. C. Chiu, M. H. Ho, and C. H. Lin,“Optimal relay antenna locationin indoor environment using particle swarm optimizer and genetic algorithm,”Wireless Personal Communications, vol.62, no.3, pp.599-615, Feb.2012.
[162] D. P. Vidyarthi, A. K. Tripathi, B. K. Sarker, and K. Rani,“Comparative study oftwo GA-based task allocation models in distributed computing system,” in Proc.4th Int. Conf. Parallel Distrib. Comput., Appl. Technol., Aug.2003, pp.458-462.
[163] W. Cheng, H. Shi, X. Yin, and D. Li,“An elitism strategy based geneticalgorithm for streaming pattern discovery in wireless sensor networks,” IEEECommun. Lett., vol.15, No.4, pp.419-421, Apr.2011.
[164] Y. Zou, Y.-D. Yao, and B. Zheng,“Cooperative relay techniques for cognitiveradio systems: spectrum sensing and secondary user transmissions,” IEEECommunications Magazine, vol.50, no.4, pp.98-103, Apr.2012.
[165] J. N. Laneman, D. N. C. Tse, and G. W. Wornell,“Cooperative diversity inwireless networks: efficient protocols and outage behavior,” IEEE Trans. Inform.Theory, vol.50, no.12, pp.3062-3080, Dec.2004.
[166] J.-B. Kim and D. Kim,“Comparison of tightly power-constrained performancesfor opportunistic amplify-and-forward relaying with partial or full channelinformation,” IEEE Commun. Lett., vol.13, no.2, pp.100-102, Feb.2009.
[167] I. Krikidis, J. Thompson, S. McLaughlin, and N. Goertz,“Amplify-and-forwardwith partial relay selection,” IEEE Commun. Lett., vol.12, no.4, pp.235-237,Apr.2008.
[168] A. Gharanjik and K. Mohamed-pour,“Switch-and-stay partial relay selectionover Rayleigh fading channels,” IET Commun., vol.5, no.9, pp.1199-1203, Jun.2011.
[169] K. B. Fredj and S. Aissa,“Performance of amplify-and-forward systems withpartial relay selection under spectrum-sharing constraints,” IEEE Trans. WirelessCommun., vol.11, no.2, pp.500-504, Feb.2012.
[170] Z. Hadzi-Velkov and N. Zlatanov,“Outage rates and outage durations ofopportunistic relaying systems,” IEEE Commun. Lett., vol.14, no.2, pp.148-150,Feb.2010.
[171] J.-B. Kim, J. Lim, and J. M. Cioffi,“Capacity scaling law in opportunisticamplify-and-forward relaying with selective ID feedback,” IEEE Commun. Lett.,vol.16, no.5, pp.589-591, May2012.
[172] I.-H. Lee and D. Kim,“Outage performance of opportunistic cooperation inamplify-and-forward relaying systems with relay selection,” IEEE Commun. Lett.,vol.16, no.2, pp.224-227, Feb.2012.
[173] F. F. Digham, M.-S. Alouini, and M. K. Simon,“On the energy detection ofunknown signals over fading channels,” IEEE Trans. Commun., vol.55, no.1, pp.21-24, Jan.2007.
[174] I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series, and Products,7thedition. San Diego, CA: Academic,2007.
[175] A. H. Nuttall,“Some integrals involving the QMfunction,” IEEE Trans. Inform.Theory, vol.21, no.1, pp.95-96, Jan.1975.
[176] D. Senaratne and C. Tellambura,“Unified exact performance analysis of two-hopamplify-and-forward relaying in Nakagami fading,” IEEE Trans. Veh. Technol.,vol.59, no.3, pp.1529-1534, Mar.2010.
[177] M. K. Simon and M.-S. Alouini, Digital Communication over Fading Channels,2nd edition. John Wiley&Sons,2005.