无线Ad Hoc网络中链路干扰与信息传输的分析及优化
|
摘要
无线Ad Hoc网络以其无中心、自组织、多跳路由的特点在众多无线网络中独树一帜,并且在军事和民用等领域得到了广泛的应用。然而,事物总是具有两面性。无线Ad Hoc网络研究中,面临着网络拓扑动态变化、节点能量有限、信道带宽有限等诸多挑战。面对这些限制,本文从改善网络的整体传输性能出发,选取两方面问题进行研究:其一,整体上如何构建干扰优化的网络拓扑;其二,局部上如何提高结构单元的传输性能。
针对整体的研究,论文从网络干扰分析入手,提出了一种新的网络干扰量化模型,并基于此给出了干扰优化的拓扑控制算法。首先,我们从理论上描述了双向链路间发生干扰的充要条件,并据此证明了在双向拓扑网络中,在双链路干扰情况下,节点使用相等功率分配策略和最小功率分配策略,对网络干扰的影响是一致的结论。接着,引入了一个新的干扰量化指标——平均部分干扰系数。理论研究与仿真分析表明,平均部分干扰系数与网络节点密度无关,可以近似表示为链路长度的线性函数。基于前述分析,后续提出了两种干扰优化拓扑控制算法——分块干扰最小算法BIMA和分布干扰最小算法LIMA。仿真结果表明,算法BIMA和LIMA不仅具有优良的抑制干扰和降低能耗的性能,而且还具备较好的spanner特性、较低的节点度以及对网络节点移动的鲁棒性。
针对局部的分析,考虑了基于三节点模型的中继网络作为研究的基本结构单元,采用渐近最优喷泉码下的协作通信技术提高其传输性能。首先,以端到端的恒定传输速率作为传输的前提,分析了二进制删除信道下,中继网络采用多种协作方式下的信道容量。结果表明,维持各信道尽可能繁忙将带来较好的中继网络特性。基于此,引入渐近最优喷泉码的概念,给出了基于中继流控制的贪婪解码转发协作方案。此后,考虑中继缓存不溢出的要求,我们利用排队理论给出了一种优化功率分配策略,并分别在加性高斯白噪声信道和瑞利衰落信道下给出了功率分配系数的数值解。仿真结果表明,该功率分配策略下的贪婪解码转发协作方案不仅满足中继缓存不溢出的要求,而且还改善了中继网络在可达速率和信噪比方面的性能。
Wireless ad hoc network is a kind of new network architecture which has no center, no organizer, and multi-hop routing. Such characteristics make it distinguish from other wireless networks and have extensive applications in both military and civilian fields. However, every coin has a flip side. Due to variable network topology, finite node energy and limited frequency bandwidth, how to improve the whole transmission performance of wireless ad hoc networks is a complicated and open problem. Facing the problem, many studies are done internally and externally, and two fundamental questions are investigated in the dissertation: the first one is how to construct a network topology with minimum interference globally; the other one is how to increase the transmission performance in a structural unit locally.
To external research, we first present a quantitative model of network interference starting from the analysis to network interference. We describe the pair-wise interference condition theoretically. By the condition, it has been proved that the interference condition is identical for two power allocation strategies: the equal-power allocation strategy and the minimum-power allocation strategy. Based on the analysis above, a new metric, the average partial interference co-efficient, is given. Theoretical research and simulation analysis indicate that the average partial interference coefficient has no relationship with node density in the network, and it can be approximated as a linear function of link distance. Then, we present two particular interference optimization topology control algorithms, BIMA (Blocked Interference Minimum Algorithm) and LIMA (Local Interference Minimum Algorithm). Simulation results show that both BIMA and LIMA can not only provide a good performance in controlling network interference and conserving node energy, but also can maintain good spanner property and keep low node degree. Besides, both BIMA and LIMA show a good robustness to node mobility.
To internal requirement, the relay network based on three nodes model is given as the basic structural unit. And we adopt cooperative communication using fountain codes to improve the transmission performance in the basic structural unit. Firstly, under the precondition of end-to-end invariable transmission rate, a simplified model is analyzed. Over binary erasure channels, the capacities of the relay network under several cooperative modes are analyzed. The results show that it will bring better transmission performance than others in the relay network if the cooperative mode can keep the status of each channel in busy mode as far as possible. According to such property, we present a greedy decode-and-forward cooperative scheme based on the flow control at the relay node after inducing the concept of the asymptotically optimal fountain codes. In the scheme, two requirements are considered. One is to prevent the relay from accumulating too many blocks because of the limited buffer size; the other one is to keep all the three channels as busy as possible in order to improve the overall throughput. To the requirements, the optimal power allocation strategy is studied by queue theory. Simulation results indicate that the greedy decode-and-forward cooperative scheme under the optimal power allocation strategy can not only keep the relay buffer from overflowing, but also improve the performances of achievable rate and bitwise signal-noise-rate in the relay network based on three nodes model.
针对整体的研究,论文从网络干扰分析入手,提出了一种新的网络干扰量化模型,并基于此给出了干扰优化的拓扑控制算法。首先,我们从理论上描述了双向链路间发生干扰的充要条件,并据此证明了在双向拓扑网络中,在双链路干扰情况下,节点使用相等功率分配策略和最小功率分配策略,对网络干扰的影响是一致的结论。接着,引入了一个新的干扰量化指标——平均部分干扰系数。理论研究与仿真分析表明,平均部分干扰系数与网络节点密度无关,可以近似表示为链路长度的线性函数。基于前述分析,后续提出了两种干扰优化拓扑控制算法——分块干扰最小算法BIMA和分布干扰最小算法LIMA。仿真结果表明,算法BIMA和LIMA不仅具有优良的抑制干扰和降低能耗的性能,而且还具备较好的spanner特性、较低的节点度以及对网络节点移动的鲁棒性。
针对局部的分析,考虑了基于三节点模型的中继网络作为研究的基本结构单元,采用渐近最优喷泉码下的协作通信技术提高其传输性能。首先,以端到端的恒定传输速率作为传输的前提,分析了二进制删除信道下,中继网络采用多种协作方式下的信道容量。结果表明,维持各信道尽可能繁忙将带来较好的中继网络特性。基于此,引入渐近最优喷泉码的概念,给出了基于中继流控制的贪婪解码转发协作方案。此后,考虑中继缓存不溢出的要求,我们利用排队理论给出了一种优化功率分配策略,并分别在加性高斯白噪声信道和瑞利衰落信道下给出了功率分配系数的数值解。仿真结果表明,该功率分配策略下的贪婪解码转发协作方案不仅满足中继缓存不溢出的要求,而且还改善了中继网络在可达速率和信噪比方面的性能。
Wireless ad hoc network is a kind of new network architecture which has no center, no organizer, and multi-hop routing. Such characteristics make it distinguish from other wireless networks and have extensive applications in both military and civilian fields. However, every coin has a flip side. Due to variable network topology, finite node energy and limited frequency bandwidth, how to improve the whole transmission performance of wireless ad hoc networks is a complicated and open problem. Facing the problem, many studies are done internally and externally, and two fundamental questions are investigated in the dissertation: the first one is how to construct a network topology with minimum interference globally; the other one is how to increase the transmission performance in a structural unit locally.
To external research, we first present a quantitative model of network interference starting from the analysis to network interference. We describe the pair-wise interference condition theoretically. By the condition, it has been proved that the interference condition is identical for two power allocation strategies: the equal-power allocation strategy and the minimum-power allocation strategy. Based on the analysis above, a new metric, the average partial interference co-efficient, is given. Theoretical research and simulation analysis indicate that the average partial interference coefficient has no relationship with node density in the network, and it can be approximated as a linear function of link distance. Then, we present two particular interference optimization topology control algorithms, BIMA (Blocked Interference Minimum Algorithm) and LIMA (Local Interference Minimum Algorithm). Simulation results show that both BIMA and LIMA can not only provide a good performance in controlling network interference and conserving node energy, but also can maintain good spanner property and keep low node degree. Besides, both BIMA and LIMA show a good robustness to node mobility.
To internal requirement, the relay network based on three nodes model is given as the basic structural unit. And we adopt cooperative communication using fountain codes to improve the transmission performance in the basic structural unit. Firstly, under the precondition of end-to-end invariable transmission rate, a simplified model is analyzed. Over binary erasure channels, the capacities of the relay network under several cooperative modes are analyzed. The results show that it will bring better transmission performance than others in the relay network if the cooperative mode can keep the status of each channel in busy mode as far as possible. According to such property, we present a greedy decode-and-forward cooperative scheme based on the flow control at the relay node after inducing the concept of the asymptotically optimal fountain codes. In the scheme, two requirements are considered. One is to prevent the relay from accumulating too many blocks because of the limited buffer size; the other one is to keep all the three channels as busy as possible in order to improve the overall throughput. To the requirements, the optimal power allocation strategy is studied by queue theory. Simulation results indicate that the greedy decode-and-forward cooperative scheme under the optimal power allocation strategy can not only keep the relay buffer from overflowing, but also improve the performances of achievable rate and bitwise signal-noise-rate in the relay network based on three nodes model.
引文
[1] Maxwell J C. A treatise on electricity and magnetism. Oxford: Clarendon Press, 1904.
[2] Hertz H R. Electric waves: being researched on the propagation of electric action with finite velocity through space. Annalen der Physik, 1888, 270(5): 155-170.
[3] Nyquist H. Certain topics in telegraph transmission theory. Trans of the American Institute of Electrical Engineers, 1928, 47(2):617-644.
[4] Shannon C E. A mathematical theory of communication. J Bell Syst Tech, 1948, 27: 379-423, 623-656.
[5] Shannon C E. Two-way communication channels. Proc of the 4th Berkeley Symp Math Stat and Prob, 1961: 611-644.
[6] Ahlswede R. Multi-way communication channels. Proc of the 2nd Int Symp Inform Theory, 1971: 23-52.
[7] Cover T, El Gamal A A. Capacity theorems for the relay channel. IEEE Trans on Inform Theory, 1975, 25(9): 572-584.
[8] Carleial A. A case where interference does not reduce capacity. IEEE Trans on Inform Theory, 1975, 21(5):569-570.
[9] Benzel R. The capacity region of a class of discrete additive degraded interference channels. IEEE Trans on Inform Theory, 1979, 25(2): 228-231.
[10] Sato H. The capacity of the Gaussian interference channel under strong interference. IEEE Trans on Inform Theory, 1981, 27(6):786-788.
[11] Cover T. Broadcast channel. IEEE Trans on Inform Theory. 1972, 18(1): 2-14.
[12]廖晓滨,赵熙.第三代移动通信网络系统技术、应用及演进.北京:人民邮电出版社, 2008.
[13]冯建和,王卫东.第三代移动网络与移动业务.北京:人民邮电出版社, 2007.
[14] http://www.ieee802.org.
[15] Anjum F, Mouchtaris P. Security for wireless Ad Hoc Networks. Wiley Publishing, 2008.
[16] Lin Y D, Hsu Y C. Multihop cellular: a new architecture for wireless communications. Proc. of IEEE Infocom, 2000: 1273-1282.
[17] Wu J, Stojmenovic I. Ad Hoc Networks. IEEE Computer Society, 2004.
[18]郑少仁,王海涛,赵志峰,等. Ad Hoc网络技术.北京:人民邮电出版社, 2005.
[19]陈林星,曾曦,曹毅.移动Ad Hoc网络:自组织分组无线网络技术.北京:电子工业出版社, 2006.
[20] Santi P. Topology control in wireless ad hoc and sensor networks. England: John Wiley&Sons Ltd, 2005.
[21] Santi P. Topology control in wireless ad hoc and sensor networks. ACM Computing Surveys, 2005, 37(2):164-194.
[22] Lloyd E L, Liu R, Marathe M V, et al. Algorithmic aspects of topology control problems for ad hoc networks. ACM Journal on Mobile Networks and Applications, 2005, 10(1-2):19-34.
[23] Alzoubi K, Li X Y, Wang Y, et al. Geometric Spanners for wireless ad hoc networks. IEEE Trans on Parallel and Distributed Syst, 2003, 14(4):408-421.
[24] Chen J, Jiang A, Kanj I, et al. Separability and topology control of quasi unit disk graphs. IEEE INFOCOM, 2007:2225-2233.
[25] Blough D M, Leoncini M, Resta G, et al. The k-Neighbors Approach to Interference Bounded and Symmetric Topology Control in Ad Hoc Networks. IEEE Trans. on Mobile Computing, 2006, 5(9):1267-1282.
[26] Penrose M. Random Geometric Graphs. Oxford: Oxford University Press, 2003.
[27] Rodoplu V, Meng T H. Minimum energy mobile wireless networks. IEEE ICC, 1998:1633-1639.
[28] Rodoplu V, Meng T H. Minimum energy mobile wireless networks. IEEE J Select Areas Commun, 1999, 17: 1333-1344.
[29] Li L, Halpern J. A minimum-energy path-preserving topology-control algorithm. IEEE Trans on Wireless Commun, 2004, 3(3):910-921.
[30] Blough D M, Harvesf C, Resta G, et al. A simulation-based study on the throughput capacity of topology control in CSMA/CA networks. IEEE Int Conf on Pervasive Computing and Commun, 2006.
[31] Behzad A, Rubin I. High transmission power increases the capacity of ad hoc wireless networks. IEEE Trans on Wireless Commun, 2006, 5(1):156-165.
[32] Gabriel K R, Sokal R R. A new statistical approach to geographic variation analysis. Systematic Zoology, 1969, 18:259-278.
[33] Toussaint G T. The relative neighborhood graph of a finite planar set. Pattern Recognition, 1980, 12:261-268.
[34] Hu L. Topology control for multihop packet radio networks. IEEE Trans on Commun, 1993, 41(10):1474-1481.
[35] Ramanathan R, Rosales-Hain R. Topology control of multiple wireless networks using transmit power adjustment. IEEE INFOCOM, 2000:404-413.
[36] Li N, Hou J C, Sha L. Design and analysis of an MST-based topology control algorithm. IEEE INFOCOM, 2003:1702-1712.
[37] Wattenhofer R, Zollinger A. XTC: a practical topology control algorithm for ad-hoc networks. Proc. of IEEE Int Parallel and Distributed Processing, 2004.
[38] Wattenhofer R, Li L, Bahl P, et al. Distributed topology control for power efficient operation in multihop wireless ad hoc networks. IEEE INFOCOM, 2001:22-26.
[39] Santi P, Blough D M, Vainstein F. A probabilistic analysis for the range assignment problem in ad hoc networks. ACM MobiHoc, 2001:212-220.
[40] Bettstetter C. On the connectivity of wireless multihop networks with homogeneous and inhomogeneous range assignment. IEEE VTC, 2002:1706-1710.
[41] Li L, Halpern J Y, Bahl P, et al. Analysis of a cone-based distributed topology control algorithm for wireless multi-hop networks. Proc of ACM Symp Principles of Distributed Computing, 2001:264-273.
[42] Li L, Halpern J Y, Bahl P, et al. A cone-based distributed topology-control algorithm for wireless multi-hop networks. IEEE/ACM Trans on Networking, 2005, 13(1):147-159.
[43] Bettstetter C, Resta G, Santi P. The node distribution of the random waypoint mobility model for wireless ad hoc networks. IEEE Trans on Mobile Comp, 2003, 2(3):257-269.
[44] Basu R, Redi J. Movement control algorithms for realization of fault-tolerant ad hoc robot networks. IEEE Network, 2004, 18(4):36-44.
[45] Huang Z, Shen C, et al. Topology control for ad hoc networks with directional antennas. Proc. of IEEE Int Conf on Comm and Networks, 2002:16-21.
[46] Li N, Hou J C, Sha L. Design and analysis of an MST-based topology control algorithm. IEEE Trans on Wireless Commun, 2005, 4(3):1195-1206.
[47] Goldsmith A. Wireless Communications. Cambridge University Press, 2005.
[48] Mark J W, Zhuang W H. Wireless communications and networking. Pearson Education, 2003.
[49] Telatar E. Capacity of multi-antenna Gaussian channels. European Trans on Telecomm, 1999, 10(6): 585-595.
[50] Foschini G J. Layered space-time architecture for wireless communications in a fading environment when using multi-element antennas. J Bell Labs Technical, 1996, 1(2):41-59.
[51] Foschini G J, Gans M J. On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Commun, 1998, 6(3):311-335.
[52] Hochwald B M, Ten Brink S. Achieving near-capacity on a multiple-antenna channel. IEEE Trans on Commun, 2003, 51(3): 389-399.
[53] Sendonaris A, Erkip E, Aazhang B. User cooperation diversity, Part I: system description. IEEE Trans on Commun, 2003, 51(11):1927-1938.
[54] Sendonaris A, Erkip E, Aazhang B. User cooperation diversity, Part II: implementation aspects and performance analysis. IEEE Trans on Commun, 2003, 51(11):1939-1948.
[55] Laneman J N, Wornell G W, Tse D N C. An efficient protocol for realizing cooperative diversity in wireless networks. Proc of IEEE ISIT, 2001.
[56] Janani M, Hedayat A, Hunter T E, et al. Coded cooperation in wireless communications: space-time transmission and iterative decoding. IEEE Trans on Signal Processing, 2004, 52(2):362-371.
[57] Hunter T E. Coded cooperation: a new framework for user cooperation in wireless systems. Ph.D. Thesis, University of Texas at Dallas, 2004.
[58] Van der Meulen E C. Three-terminal communication channels. Adv Appl Prob, 1971, 3:120-154.
[59] Cover T M. Broadcast channels. IEEE Trans on Inform Theory, 1972, 18(1):2-14.
[60] Cover T M. An achievable rate region for the broadcast channels. IEEE Trans on Inform Theory, 1975, 21(4):399-404.
[61] Bletsas A, Shin H, Win M. Cooperative communications with outage-optimal opportunistic relaying. IEEE Trans on Wireless Commun, 2007, 6(9):3450-3460.
[62] Cover T M, Leung G S L. An achievable rate region for the multiple-access channel with feedback. IEEE Trans on Inform Theory, 1981, 27(3):292-298.
[63] Cover T M. Comments on broadcast channels. IEEE Trans. on Inform Theory, 1998, 44(6):2524-2530.
[64] Hajek B, Pursley M B. Evaluation of an achievable rate region for the broadcast channel. IEEE Trans on Inform Theory, 1979, 25(1):36-46.
[65] Ozarow L H. The capacity of the white Gaussian multiple access channel with feedback. IEEE Trans on Inform Theory, 1984, 30(4):623-629.
[66] Gupta P, Kumar P R. The Capacity of Wireless Networks. IEEE Trans. on Inform. Theory, 2000, 46(2):388-404.
[67] Gupta P, Kumar P R. Towards an information theory of large networks: an achievable rate region. IEEE Trans on Inform Theory, 2003, 49(8):1877-1894.
[68] Zheng L, Tse D N C. Diversity and multiplexing: a fundamental tradeoff in multiple antenna channels. IEEE Trans on Inform Theory, 2003, 49(5):1073-1096.
[69] Tse D N C, Viswanath P, Zheng L. Diversity-multiplexing tradeoff in multiple-access channels. IEEE Trans on Inform Theory, 2004, 50(9):1859-1874.
[70] Azarian K, El-Gamal H, Schniter P. On the achievable diversity-multiplexing tradeoff in half-duplexing cooperative channels. IEEE Trans on Inform Theory, 2005, 51(12):4152-4172.
[71] Narasimhan R. Finite-SNR diversity-multiplexing tradeoff for correlated rayleigh and rician MIMO channels. IEEE Trans on Inform Theory, 2006, 52(9):3965-3979.
[72] Stauffer E, Oyman O, Narasimhan R, et al. Finite-SNR diversity-multiplexing tradeoffs in fading relay channels. IEEE J on Sel Areas Commun, 2007, 25(2):245-257.
[73] Azarian K, El-Gamal H. The throughput-reliability tradeoff in block fading MIMO channels. IEEE Trans on Inform Theory, 2007, 53(2):488-501.
[74] Tarokh V, Seshadri N, Calderbank A R. Space-time codes for high data rate wireless communications: performance criterion and code construction. IEEE Trans on Inform Theory, 1998, 44(2):744-765.
[75] Tarokh V, Seshadri N, Calderbank A R. Space-time block codes from orthogonal designs. IEEE Trans on Inform Theory, 1999, 45(5):1456-1467.
[76] Tarokh V, Jafarkhani H, Calderbank A R. Space-time block coding for wireless communications: performance results. IEEE J on Sel Areas Commun, 1999, 17(3):451-460.
[77] Tarokh V, Jafarkhani H. A differential detection scheme for transmit diversity. IEEE J on Sel Areas Commun, 2000, 18(7):1169-1174.
[78] Foschini G J, Gans M J. On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Commun, 1998:311-335.
[79] Foschini G J, Golden G D, Valenzuela R A, et al. Simplified processing for high spectral efficiency wireless communication employing multi-element arrays. IEEE J on Sel Areas Commun, 1999, 17(11):1841-1851.
[80] Hassibi B, Hochwald B M. Linear dispersion codes. IEEE Int Symp on Inform Theory, 2001.
[81] Hassibi B, Hochwald B M. High-rate codes that are linear in space and time. IEEE Trans on Inform Theory, 2002, 48(7):1804-1824.
[82] Health R W, Paulraj A J. Linear dispersion codes for MIMO systems based on frame theory. IEEE Trans on Signal Processing, 2002, 50(10):2429-2441.
[83] Zhang J, Liu J, Wong K M. Trace-orthogonal full-diversity cyclotomic space-time codes. IEEE Trans on Signal Processing, 2007, 55(2):618-630.
[84] Laneman J N, Wornell G W, Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks. IEEE Trans on Inform Theory, 2003, 49(10): 2415-2425.
[85] Nabar R U, Kneubuhler F W, Aolcskei H B. Performance limits of amplify-and-forward based fading relay channels. Proc. of IEEE Int Conf. Acoustics, Speech and Signal Processing, 2004:565-568.
[86] Nabar R U, Aolcskei H B, Kneubuhler F W. Fading relay channels: performance limits and space-time signal design. IEEE J on Sel Areas Commun, 2004, 22(6):1099-1109.
[87] Azarian K, El-Gamal H, Schniter P. On the achievable diversity-multiplexing tradeoff in half-duplexing cooperative channels. IEEE Trans on Inform Theory, 2005, 51(12): 4152-4172.
[88] Yang S, Belfiore J C. Towards the optimal amplify-and-forward cooperative diversity scheme. IEEE Trans on Inform Theory, 2007, 53(9): 3114-3126.
[89] Yang S, Belfiore J C. Optimal space-time codes for the MIMO amplify-and-forward cooperative channel. IEEE Trans on Inform Theory, 2007, 53(2):674-663.
[90] Jing Y, Hassibi B. Distributed space-time coding in wireless relay networks. IEEE Trans on Wireless Commun, 2006, 5:3524-3536.
[91] Liang K, Wang X, Berenguer I. Minimum error-rate linear dispersion codes for cooperative relays. IEEE Trans on Vehicular Tech, 2007, 56(4):2143-2157.
[92] Ding Y, Zhang J, Wong K M. The amplify-and-forward half-duplex cooperative system: pairwise error probability and precoder design. IEEE Trans on Signal Processing, 2007, 55(2):605-617.
[93] Hunter T E, Nosratinia A. Cooperative diversity through coding. IEEE Int Symp Inform Theory, 2002.
[94] Hunter T E, Nosratinia A. Diversity through coded cooperation. IEEE Trans on Wireless Commun, 2006, 5(2):283-289.
[95] Hunter T E, Sanayei S, Nosratinia A. Outage analysis of coded cooperation. IEEE Trans on Inform Theory, 2006, 52(2): 375-391.
[96] Li C, Yue G, Khojastepour M A, et al. LDPC-coded cooperative relay systems: performance analysis and code design. IEEE Trans on Commun, 2008, 56(3):485-496.
[97] Zhang Z, Duman T M. Capacity-approaching turbo coding and iterative decoding for relaychannels. IEEE Trans on Commun, 2005, 53(11):1895-1905.
[98] Li Y, Vucetic B, Wong T F, et al. Distributed turbo coding with soft information relaying in multihop relay networks. IEEE J Selected Areas Commun, 2006, 24(11):2040-2050.
[99] Castura J, Mao Y. Rateless coding for wireless relay channels. Proc of IEEE Int Symp Inform Theory, 2005:810-814.
[100] Castura J, Mao Y. Rateless coding over fading channels. IEEE Commun Letter, 2006, 10:46-48.
[101] Molisch A F, Neelesh B, Yedidia J S, et al. Cooperative relay networks using fountain codes. Proc of Global Telecommun, 2006:1-6.
[102] Mitran P, Ochiai H, Tarokh V. Performance of fountain codes in collaborative relay networks. IEEE Trans on Wireless Commun, 2007, 6(11):4108-4119.
[103] Liu Y. A low complexity protocol for relay channels employing rateless codes and acknowledgement. IEEE Int Symp on Inform Theory, 2006.
[104] Zhang S, Liew S C, Lam P. Physical layer network coding. Proc. Int Conf on Mobile Computing and Networking, 2006.
[105] Popovski P, Yomo H. Wireless network coding by amplify-and-forward for bi-directional traffic flows. IEEE Commun Letter, 2007, 11(1):16-18.
[106] Popovski P, Yomo H. Physical network coding in two-way wireless relay channels. IEEE ICC, 2007:707-712.
[107] Wu Y, Chou P A, Kung S. Information exchange in wireless with network coding and physical-layer broadcast. Proc Conf Inform Sci. and Systems, 2005.
[108] Hausl C, Dupraz P. Iterative network and channel decoding for the two-way relay channel. IEEE ICC, 2006:1568-1573.
[109] Hausl C, Dupraz P. Joint network-channel coding for the multiple-access relay channel. IEEE Conf on Sensor and Ad Hoc Commun and Networks, 2006:817-822.
[110] Zhang S, Zhu Y, Liew S C, et al. Joint design of network coding and channel decoding for wireless networks. IEEE WCNC, 2007:779-784.
[111] Gallager R G. A perspective on multiaccess channels. IEEE Trans on Inform Theory, 1999, 31(2):124-142.
[112] Rimoldi B, Urbanke R. A rate-splitting approach to the gaussian multiple-access channel. IEEE Trans on Inform Theory, 1996, 42(2):364-375.
[113] Tse D N C, Hanly S V. Multiaccess fading channels-Part I: polymatroid structure, optimal resource allocation and throughput capacities. IEEE Trans on Inform Theory, 1998, 44(7):2796-2815.
[114] Hanly S V, Tse D N C. Multiaccess fading channels-Part II: delay-limited capacities. IEEE Trans on Inform Theory, 1998, 44(7):2816-2831.
[115] Jindal N, Vishwanath S, Goldsmith A. On the duality of gaussian multiple-access and broadcast channels. IEEE Trans on Inform Theory, 2004, 50(5):768-783.
[116] Cao J, Yeh E M. Asymptotically optimal multiple-access communication via distributed rate splitting. IEEE Trans on Inform Theory, 2007, 53(1):304-319.
[117] Goldsmith A J, Varaiya P P. Capacity of fading channels with channel side information. IEEE Trans on Inform Theory, 1997, 43(6):1986-1992.
[118] Caire G, Taricco G, Biglieri E. Optimum power control over fading channels. IEEE Trans on Inform Theory, 1999, 45(5):1468-1489.
[119] Scaglione A, Stoica P, Barbarossa S, et al. Optimal designs for space-time linear precoders and decoders. IEEE Trans on Signal Processing, 2007, 50(5):1051-1064.
[120] Bilieri E, Caire G, Taricco G. Limiting performance of block fading channels with multiple antennas. IEEE Trans on Inform Theory, 2001, 47(4):1273-1289.
[121] Kose C, Goeckel D L. On power adaptation in adaptive signaling systems. IEEE Trans on Commun, 2000, 48(11):1769-1773.
[122] Chiu-Yam Ng T, Yu W. Joint optimization of relay strategies and resource allocations in cooperative cellular networks. IEEE J Selected Areas Commun, 2007, 25(2):328-339.
[123] Luo J, Blum R S, Cimini L J, et al. Decode-and-forward cooperative diversity with power allocation in wireless networks. IEEE Trans on Wireless Commun, 2007, 6(3):793-799.
[124] Vucetic B, Zhou Z, Dohler M. Distributed adaptive power allocation for wireless relay networks. IEEE Trans on Wireless Commun, 2007, 6(3):948-958.
[125] Gunduz D, Erkip E. Opportunistic cooperation by dynamic resource allocation. IEEE Trans on Wireless Commun, 2007, 6(4):1446-1454.
[126] Tang J, Zhang X. Cross-layer resource allocation over wireless relay networks for quality of service provisioning. IEEE J Selected Areas Commun, 2007, 25(5):645-656.
[127] Ahmed N, Aazhang B. Throughput gains using rate and power control in cooperative relay networks. IEEE Trans on Wireless Commun, 2007, 55(4):656-660.
[128] Liang Y, Veeravalli V V, Vincent Poor H. Resource allocation for wireless fading relay channels: max-min solution. IEEE Trans on Inform Theory, 2007, 53(10):3432-3453.
[129] Chen M, Serbetli S, Yener A. Distributed power allocation strategies for parallel relay networks. IEEE Trans on Wireless Commun, 2008, 7(2):552-561.
[130] Cho W, Yang L. Resource allocation for amplify-and-forward relay networks with differential modulation. IEEE Globecom, 2007.
[131] Himsoon T, Su W, Liu K. Differential modulation for multimode amplify-and-forward wireless relay networks. IEEE WCNC, 2006.
[132] Annavajjlal R, Cosman P C, Milstein L B. Statistical channel knowledge-based optimum power allocation for relaying protocols in the high SNR regime. IEEE J Selected Areas Commun, 2007, 25(2):292-305.
[133] Yi Z, Kim I. Joint optimization of relay-precoders and decoders with partial channel side information in cooperative networks. IEEE J Selected Areas Commun, 2007, 25(2): 447-458.
[134] Zhao Y, Adve R, Lim T J. Beamforming with limited feedback in amplify-and-forward cooperative networks. IEEE GlobeCom, 2007:3457-3461.
[135] Burkhart M, Rickenbach P, Wattenhofer R, et al. Does topology control reduce interference. Proc ACM Int Symp on Mobile Ad-hoc Networking and Computing, 2004:9-19.
[136] Rickenbach P, Schmid S, Wattenhofer R, et al. A robust interference model for wireless ad-hoc networks. Proc IEEE Int Parallel and Distributed Processing Symp, 2005.
[137] Moaveni-Nejad K, Li X. Low interference topology control for wireless ad hoc networks. Ad Hoc and Sensor Wireless Networks, 2004.
[138] Johansson T, Carr-Motyckova L. Reducing interference in ad hoc networks through topology control. Workshop on Discrete Algo and Meth for Mobile Computing and Commun, 2005.
[139] Meyer F, Schindelhauer C, Volbert K, et al. Energy, congestion and dilation in radio networks. Proc of the 14th ACM Symp on Parallel Algorithm and Architecture, 2002.
[140] Narayanaswamy S, Kawadia V, Sreenivas R S, et al. Power control in ad-hoc networks: theory, architecture, algorithm and implementation of the COMPOW protocol. Proc of the European Wireless Conf, 2002:156-162.
[141] Kawadia V, Kumar P R. Principles and protocols for power control in ad hoc networks. IEEE J Selected Areas in Commun, 2005, 23(5):76-88.
[142] Agarwal S, Krishnamurthy S V, Katz R H, et al. Distributed power control in ad-hoc wireless networks. Personal Indoor Mobile Radio Conf, 2001.
[143] Li Q, Fan P Y, Wu D O. Energy efficient routing in ad hoc networks with Nakagami-m fading channels. IEEE ICC, 2009:1-6.
[144] Jenkac H, Mayer T, Stockhammer T, et al. Soft decoding of LT-codes for wireless broadcast. Proc IST Mobile Summit, 2005.
[145] Byers J, Luby M, Mitzenmacher M, et al. A digital fountain approach to reliable distribution of bulk data. Conf SIGCOMM, 1998:56-67.
[146] Luby M. LT codes. IEEE Symposium on Foundations of Computer Science, 2002.
[147] Shokrollahi A. Raptor codes. IEEE Int Symp on Inform Theory, 2004.
[148] Etasami O, Molkaraie M, Shokrollahi A. Raptor codes on symmetric channels. IEEE Int Symp on Inform Theory, 2004:38.
[149] Palanki R, Yedidia J. Rateless codes on noisiy channels. Proc. Int Symp on Inform Theory, 2004.
[150] Gallager R G. Low-density parity-check codes. IEEE Trans on Inform Theory, 1962, 8(1):21-28.
[151] Tanner R M. A recursive approach to low complexity codes. IEEE Trans on Inform Theory, 1981, 27(5):534-547.
[152] Morelos-Zaragoza R H. The art of error correcting coding. John Wiley & Sons, 2006.
[153] Chakrabarti A, Baynast A, Sabharwal A, et al. Low density parity check codes for the relay channel. IEEE J Selected Areas Commun, 2007, 25(2):280-291.
[154] Host-Madsen A, Zhang J. Capacity bounds and power allocation for the wireless relay channel. IEEE Trans on Inform Thoery, 2005, 51(6):2020-2040.
[155] Asmussen S. Applied Probability and Queues. Springer, 2003.
[156] McEliece R, Stark W. Channels with block interference. IEEE Trans on Inform. Theory, 1984, 30(1):44-53.
[2] Hertz H R. Electric waves: being researched on the propagation of electric action with finite velocity through space. Annalen der Physik, 1888, 270(5): 155-170.
[3] Nyquist H. Certain topics in telegraph transmission theory. Trans of the American Institute of Electrical Engineers, 1928, 47(2):617-644.
[4] Shannon C E. A mathematical theory of communication. J Bell Syst Tech, 1948, 27: 379-423, 623-656.
[5] Shannon C E. Two-way communication channels. Proc of the 4th Berkeley Symp Math Stat and Prob, 1961: 611-644.
[6] Ahlswede R. Multi-way communication channels. Proc of the 2nd Int Symp Inform Theory, 1971: 23-52.
[7] Cover T, El Gamal A A. Capacity theorems for the relay channel. IEEE Trans on Inform Theory, 1975, 25(9): 572-584.
[8] Carleial A. A case where interference does not reduce capacity. IEEE Trans on Inform Theory, 1975, 21(5):569-570.
[9] Benzel R. The capacity region of a class of discrete additive degraded interference channels. IEEE Trans on Inform Theory, 1979, 25(2): 228-231.
[10] Sato H. The capacity of the Gaussian interference channel under strong interference. IEEE Trans on Inform Theory, 1981, 27(6):786-788.
[11] Cover T. Broadcast channel. IEEE Trans on Inform Theory. 1972, 18(1): 2-14.
[12]廖晓滨,赵熙.第三代移动通信网络系统技术、应用及演进.北京:人民邮电出版社, 2008.
[13]冯建和,王卫东.第三代移动网络与移动业务.北京:人民邮电出版社, 2007.
[14] http://www.ieee802.org.
[15] Anjum F, Mouchtaris P. Security for wireless Ad Hoc Networks. Wiley Publishing, 2008.
[16] Lin Y D, Hsu Y C. Multihop cellular: a new architecture for wireless communications. Proc. of IEEE Infocom, 2000: 1273-1282.
[17] Wu J, Stojmenovic I. Ad Hoc Networks. IEEE Computer Society, 2004.
[18]郑少仁,王海涛,赵志峰,等. Ad Hoc网络技术.北京:人民邮电出版社, 2005.
[19]陈林星,曾曦,曹毅.移动Ad Hoc网络:自组织分组无线网络技术.北京:电子工业出版社, 2006.
[20] Santi P. Topology control in wireless ad hoc and sensor networks. England: John Wiley&Sons Ltd, 2005.
[21] Santi P. Topology control in wireless ad hoc and sensor networks. ACM Computing Surveys, 2005, 37(2):164-194.
[22] Lloyd E L, Liu R, Marathe M V, et al. Algorithmic aspects of topology control problems for ad hoc networks. ACM Journal on Mobile Networks and Applications, 2005, 10(1-2):19-34.
[23] Alzoubi K, Li X Y, Wang Y, et al. Geometric Spanners for wireless ad hoc networks. IEEE Trans on Parallel and Distributed Syst, 2003, 14(4):408-421.
[24] Chen J, Jiang A, Kanj I, et al. Separability and topology control of quasi unit disk graphs. IEEE INFOCOM, 2007:2225-2233.
[25] Blough D M, Leoncini M, Resta G, et al. The k-Neighbors Approach to Interference Bounded and Symmetric Topology Control in Ad Hoc Networks. IEEE Trans. on Mobile Computing, 2006, 5(9):1267-1282.
[26] Penrose M. Random Geometric Graphs. Oxford: Oxford University Press, 2003.
[27] Rodoplu V, Meng T H. Minimum energy mobile wireless networks. IEEE ICC, 1998:1633-1639.
[28] Rodoplu V, Meng T H. Minimum energy mobile wireless networks. IEEE J Select Areas Commun, 1999, 17: 1333-1344.
[29] Li L, Halpern J. A minimum-energy path-preserving topology-control algorithm. IEEE Trans on Wireless Commun, 2004, 3(3):910-921.
[30] Blough D M, Harvesf C, Resta G, et al. A simulation-based study on the throughput capacity of topology control in CSMA/CA networks. IEEE Int Conf on Pervasive Computing and Commun, 2006.
[31] Behzad A, Rubin I. High transmission power increases the capacity of ad hoc wireless networks. IEEE Trans on Wireless Commun, 2006, 5(1):156-165.
[32] Gabriel K R, Sokal R R. A new statistical approach to geographic variation analysis. Systematic Zoology, 1969, 18:259-278.
[33] Toussaint G T. The relative neighborhood graph of a finite planar set. Pattern Recognition, 1980, 12:261-268.
[34] Hu L. Topology control for multihop packet radio networks. IEEE Trans on Commun, 1993, 41(10):1474-1481.
[35] Ramanathan R, Rosales-Hain R. Topology control of multiple wireless networks using transmit power adjustment. IEEE INFOCOM, 2000:404-413.
[36] Li N, Hou J C, Sha L. Design and analysis of an MST-based topology control algorithm. IEEE INFOCOM, 2003:1702-1712.
[37] Wattenhofer R, Zollinger A. XTC: a practical topology control algorithm for ad-hoc networks. Proc. of IEEE Int Parallel and Distributed Processing, 2004.
[38] Wattenhofer R, Li L, Bahl P, et al. Distributed topology control for power efficient operation in multihop wireless ad hoc networks. IEEE INFOCOM, 2001:22-26.
[39] Santi P, Blough D M, Vainstein F. A probabilistic analysis for the range assignment problem in ad hoc networks. ACM MobiHoc, 2001:212-220.
[40] Bettstetter C. On the connectivity of wireless multihop networks with homogeneous and inhomogeneous range assignment. IEEE VTC, 2002:1706-1710.
[41] Li L, Halpern J Y, Bahl P, et al. Analysis of a cone-based distributed topology control algorithm for wireless multi-hop networks. Proc of ACM Symp Principles of Distributed Computing, 2001:264-273.
[42] Li L, Halpern J Y, Bahl P, et al. A cone-based distributed topology-control algorithm for wireless multi-hop networks. IEEE/ACM Trans on Networking, 2005, 13(1):147-159.
[43] Bettstetter C, Resta G, Santi P. The node distribution of the random waypoint mobility model for wireless ad hoc networks. IEEE Trans on Mobile Comp, 2003, 2(3):257-269.
[44] Basu R, Redi J. Movement control algorithms for realization of fault-tolerant ad hoc robot networks. IEEE Network, 2004, 18(4):36-44.
[45] Huang Z, Shen C, et al. Topology control for ad hoc networks with directional antennas. Proc. of IEEE Int Conf on Comm and Networks, 2002:16-21.
[46] Li N, Hou J C, Sha L. Design and analysis of an MST-based topology control algorithm. IEEE Trans on Wireless Commun, 2005, 4(3):1195-1206.
[47] Goldsmith A. Wireless Communications. Cambridge University Press, 2005.
[48] Mark J W, Zhuang W H. Wireless communications and networking. Pearson Education, 2003.
[49] Telatar E. Capacity of multi-antenna Gaussian channels. European Trans on Telecomm, 1999, 10(6): 585-595.
[50] Foschini G J. Layered space-time architecture for wireless communications in a fading environment when using multi-element antennas. J Bell Labs Technical, 1996, 1(2):41-59.
[51] Foschini G J, Gans M J. On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Commun, 1998, 6(3):311-335.
[52] Hochwald B M, Ten Brink S. Achieving near-capacity on a multiple-antenna channel. IEEE Trans on Commun, 2003, 51(3): 389-399.
[53] Sendonaris A, Erkip E, Aazhang B. User cooperation diversity, Part I: system description. IEEE Trans on Commun, 2003, 51(11):1927-1938.
[54] Sendonaris A, Erkip E, Aazhang B. User cooperation diversity, Part II: implementation aspects and performance analysis. IEEE Trans on Commun, 2003, 51(11):1939-1948.
[55] Laneman J N, Wornell G W, Tse D N C. An efficient protocol for realizing cooperative diversity in wireless networks. Proc of IEEE ISIT, 2001.
[56] Janani M, Hedayat A, Hunter T E, et al. Coded cooperation in wireless communications: space-time transmission and iterative decoding. IEEE Trans on Signal Processing, 2004, 52(2):362-371.
[57] Hunter T E. Coded cooperation: a new framework for user cooperation in wireless systems. Ph.D. Thesis, University of Texas at Dallas, 2004.
[58] Van der Meulen E C. Three-terminal communication channels. Adv Appl Prob, 1971, 3:120-154.
[59] Cover T M. Broadcast channels. IEEE Trans on Inform Theory, 1972, 18(1):2-14.
[60] Cover T M. An achievable rate region for the broadcast channels. IEEE Trans on Inform Theory, 1975, 21(4):399-404.
[61] Bletsas A, Shin H, Win M. Cooperative communications with outage-optimal opportunistic relaying. IEEE Trans on Wireless Commun, 2007, 6(9):3450-3460.
[62] Cover T M, Leung G S L. An achievable rate region for the multiple-access channel with feedback. IEEE Trans on Inform Theory, 1981, 27(3):292-298.
[63] Cover T M. Comments on broadcast channels. IEEE Trans. on Inform Theory, 1998, 44(6):2524-2530.
[64] Hajek B, Pursley M B. Evaluation of an achievable rate region for the broadcast channel. IEEE Trans on Inform Theory, 1979, 25(1):36-46.
[65] Ozarow L H. The capacity of the white Gaussian multiple access channel with feedback. IEEE Trans on Inform Theory, 1984, 30(4):623-629.
[66] Gupta P, Kumar P R. The Capacity of Wireless Networks. IEEE Trans. on Inform. Theory, 2000, 46(2):388-404.
[67] Gupta P, Kumar P R. Towards an information theory of large networks: an achievable rate region. IEEE Trans on Inform Theory, 2003, 49(8):1877-1894.
[68] Zheng L, Tse D N C. Diversity and multiplexing: a fundamental tradeoff in multiple antenna channels. IEEE Trans on Inform Theory, 2003, 49(5):1073-1096.
[69] Tse D N C, Viswanath P, Zheng L. Diversity-multiplexing tradeoff in multiple-access channels. IEEE Trans on Inform Theory, 2004, 50(9):1859-1874.
[70] Azarian K, El-Gamal H, Schniter P. On the achievable diversity-multiplexing tradeoff in half-duplexing cooperative channels. IEEE Trans on Inform Theory, 2005, 51(12):4152-4172.
[71] Narasimhan R. Finite-SNR diversity-multiplexing tradeoff for correlated rayleigh and rician MIMO channels. IEEE Trans on Inform Theory, 2006, 52(9):3965-3979.
[72] Stauffer E, Oyman O, Narasimhan R, et al. Finite-SNR diversity-multiplexing tradeoffs in fading relay channels. IEEE J on Sel Areas Commun, 2007, 25(2):245-257.
[73] Azarian K, El-Gamal H. The throughput-reliability tradeoff in block fading MIMO channels. IEEE Trans on Inform Theory, 2007, 53(2):488-501.
[74] Tarokh V, Seshadri N, Calderbank A R. Space-time codes for high data rate wireless communications: performance criterion and code construction. IEEE Trans on Inform Theory, 1998, 44(2):744-765.
[75] Tarokh V, Seshadri N, Calderbank A R. Space-time block codes from orthogonal designs. IEEE Trans on Inform Theory, 1999, 45(5):1456-1467.
[76] Tarokh V, Jafarkhani H, Calderbank A R. Space-time block coding for wireless communications: performance results. IEEE J on Sel Areas Commun, 1999, 17(3):451-460.
[77] Tarokh V, Jafarkhani H. A differential detection scheme for transmit diversity. IEEE J on Sel Areas Commun, 2000, 18(7):1169-1174.
[78] Foschini G J, Gans M J. On limits of wireless communications in a fading environment when using multiple antennas. Wireless Personal Commun, 1998:311-335.
[79] Foschini G J, Golden G D, Valenzuela R A, et al. Simplified processing for high spectral efficiency wireless communication employing multi-element arrays. IEEE J on Sel Areas Commun, 1999, 17(11):1841-1851.
[80] Hassibi B, Hochwald B M. Linear dispersion codes. IEEE Int Symp on Inform Theory, 2001.
[81] Hassibi B, Hochwald B M. High-rate codes that are linear in space and time. IEEE Trans on Inform Theory, 2002, 48(7):1804-1824.
[82] Health R W, Paulraj A J. Linear dispersion codes for MIMO systems based on frame theory. IEEE Trans on Signal Processing, 2002, 50(10):2429-2441.
[83] Zhang J, Liu J, Wong K M. Trace-orthogonal full-diversity cyclotomic space-time codes. IEEE Trans on Signal Processing, 2007, 55(2):618-630.
[84] Laneman J N, Wornell G W, Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks. IEEE Trans on Inform Theory, 2003, 49(10): 2415-2425.
[85] Nabar R U, Kneubuhler F W, Aolcskei H B. Performance limits of amplify-and-forward based fading relay channels. Proc. of IEEE Int Conf. Acoustics, Speech and Signal Processing, 2004:565-568.
[86] Nabar R U, Aolcskei H B, Kneubuhler F W. Fading relay channels: performance limits and space-time signal design. IEEE J on Sel Areas Commun, 2004, 22(6):1099-1109.
[87] Azarian K, El-Gamal H, Schniter P. On the achievable diversity-multiplexing tradeoff in half-duplexing cooperative channels. IEEE Trans on Inform Theory, 2005, 51(12): 4152-4172.
[88] Yang S, Belfiore J C. Towards the optimal amplify-and-forward cooperative diversity scheme. IEEE Trans on Inform Theory, 2007, 53(9): 3114-3126.
[89] Yang S, Belfiore J C. Optimal space-time codes for the MIMO amplify-and-forward cooperative channel. IEEE Trans on Inform Theory, 2007, 53(2):674-663.
[90] Jing Y, Hassibi B. Distributed space-time coding in wireless relay networks. IEEE Trans on Wireless Commun, 2006, 5:3524-3536.
[91] Liang K, Wang X, Berenguer I. Minimum error-rate linear dispersion codes for cooperative relays. IEEE Trans on Vehicular Tech, 2007, 56(4):2143-2157.
[92] Ding Y, Zhang J, Wong K M. The amplify-and-forward half-duplex cooperative system: pairwise error probability and precoder design. IEEE Trans on Signal Processing, 2007, 55(2):605-617.
[93] Hunter T E, Nosratinia A. Cooperative diversity through coding. IEEE Int Symp Inform Theory, 2002.
[94] Hunter T E, Nosratinia A. Diversity through coded cooperation. IEEE Trans on Wireless Commun, 2006, 5(2):283-289.
[95] Hunter T E, Sanayei S, Nosratinia A. Outage analysis of coded cooperation. IEEE Trans on Inform Theory, 2006, 52(2): 375-391.
[96] Li C, Yue G, Khojastepour M A, et al. LDPC-coded cooperative relay systems: performance analysis and code design. IEEE Trans on Commun, 2008, 56(3):485-496.
[97] Zhang Z, Duman T M. Capacity-approaching turbo coding and iterative decoding for relaychannels. IEEE Trans on Commun, 2005, 53(11):1895-1905.
[98] Li Y, Vucetic B, Wong T F, et al. Distributed turbo coding with soft information relaying in multihop relay networks. IEEE J Selected Areas Commun, 2006, 24(11):2040-2050.
[99] Castura J, Mao Y. Rateless coding for wireless relay channels. Proc of IEEE Int Symp Inform Theory, 2005:810-814.
[100] Castura J, Mao Y. Rateless coding over fading channels. IEEE Commun Letter, 2006, 10:46-48.
[101] Molisch A F, Neelesh B, Yedidia J S, et al. Cooperative relay networks using fountain codes. Proc of Global Telecommun, 2006:1-6.
[102] Mitran P, Ochiai H, Tarokh V. Performance of fountain codes in collaborative relay networks. IEEE Trans on Wireless Commun, 2007, 6(11):4108-4119.
[103] Liu Y. A low complexity protocol for relay channels employing rateless codes and acknowledgement. IEEE Int Symp on Inform Theory, 2006.
[104] Zhang S, Liew S C, Lam P. Physical layer network coding. Proc. Int Conf on Mobile Computing and Networking, 2006.
[105] Popovski P, Yomo H. Wireless network coding by amplify-and-forward for bi-directional traffic flows. IEEE Commun Letter, 2007, 11(1):16-18.
[106] Popovski P, Yomo H. Physical network coding in two-way wireless relay channels. IEEE ICC, 2007:707-712.
[107] Wu Y, Chou P A, Kung S. Information exchange in wireless with network coding and physical-layer broadcast. Proc Conf Inform Sci. and Systems, 2005.
[108] Hausl C, Dupraz P. Iterative network and channel decoding for the two-way relay channel. IEEE ICC, 2006:1568-1573.
[109] Hausl C, Dupraz P. Joint network-channel coding for the multiple-access relay channel. IEEE Conf on Sensor and Ad Hoc Commun and Networks, 2006:817-822.
[110] Zhang S, Zhu Y, Liew S C, et al. Joint design of network coding and channel decoding for wireless networks. IEEE WCNC, 2007:779-784.
[111] Gallager R G. A perspective on multiaccess channels. IEEE Trans on Inform Theory, 1999, 31(2):124-142.
[112] Rimoldi B, Urbanke R. A rate-splitting approach to the gaussian multiple-access channel. IEEE Trans on Inform Theory, 1996, 42(2):364-375.
[113] Tse D N C, Hanly S V. Multiaccess fading channels-Part I: polymatroid structure, optimal resource allocation and throughput capacities. IEEE Trans on Inform Theory, 1998, 44(7):2796-2815.
[114] Hanly S V, Tse D N C. Multiaccess fading channels-Part II: delay-limited capacities. IEEE Trans on Inform Theory, 1998, 44(7):2816-2831.
[115] Jindal N, Vishwanath S, Goldsmith A. On the duality of gaussian multiple-access and broadcast channels. IEEE Trans on Inform Theory, 2004, 50(5):768-783.
[116] Cao J, Yeh E M. Asymptotically optimal multiple-access communication via distributed rate splitting. IEEE Trans on Inform Theory, 2007, 53(1):304-319.
[117] Goldsmith A J, Varaiya P P. Capacity of fading channels with channel side information. IEEE Trans on Inform Theory, 1997, 43(6):1986-1992.
[118] Caire G, Taricco G, Biglieri E. Optimum power control over fading channels. IEEE Trans on Inform Theory, 1999, 45(5):1468-1489.
[119] Scaglione A, Stoica P, Barbarossa S, et al. Optimal designs for space-time linear precoders and decoders. IEEE Trans on Signal Processing, 2007, 50(5):1051-1064.
[120] Bilieri E, Caire G, Taricco G. Limiting performance of block fading channels with multiple antennas. IEEE Trans on Inform Theory, 2001, 47(4):1273-1289.
[121] Kose C, Goeckel D L. On power adaptation in adaptive signaling systems. IEEE Trans on Commun, 2000, 48(11):1769-1773.
[122] Chiu-Yam Ng T, Yu W. Joint optimization of relay strategies and resource allocations in cooperative cellular networks. IEEE J Selected Areas Commun, 2007, 25(2):328-339.
[123] Luo J, Blum R S, Cimini L J, et al. Decode-and-forward cooperative diversity with power allocation in wireless networks. IEEE Trans on Wireless Commun, 2007, 6(3):793-799.
[124] Vucetic B, Zhou Z, Dohler M. Distributed adaptive power allocation for wireless relay networks. IEEE Trans on Wireless Commun, 2007, 6(3):948-958.
[125] Gunduz D, Erkip E. Opportunistic cooperation by dynamic resource allocation. IEEE Trans on Wireless Commun, 2007, 6(4):1446-1454.
[126] Tang J, Zhang X. Cross-layer resource allocation over wireless relay networks for quality of service provisioning. IEEE J Selected Areas Commun, 2007, 25(5):645-656.
[127] Ahmed N, Aazhang B. Throughput gains using rate and power control in cooperative relay networks. IEEE Trans on Wireless Commun, 2007, 55(4):656-660.
[128] Liang Y, Veeravalli V V, Vincent Poor H. Resource allocation for wireless fading relay channels: max-min solution. IEEE Trans on Inform Theory, 2007, 53(10):3432-3453.
[129] Chen M, Serbetli S, Yener A. Distributed power allocation strategies for parallel relay networks. IEEE Trans on Wireless Commun, 2008, 7(2):552-561.
[130] Cho W, Yang L. Resource allocation for amplify-and-forward relay networks with differential modulation. IEEE Globecom, 2007.
[131] Himsoon T, Su W, Liu K. Differential modulation for multimode amplify-and-forward wireless relay networks. IEEE WCNC, 2006.
[132] Annavajjlal R, Cosman P C, Milstein L B. Statistical channel knowledge-based optimum power allocation for relaying protocols in the high SNR regime. IEEE J Selected Areas Commun, 2007, 25(2):292-305.
[133] Yi Z, Kim I. Joint optimization of relay-precoders and decoders with partial channel side information in cooperative networks. IEEE J Selected Areas Commun, 2007, 25(2): 447-458.
[134] Zhao Y, Adve R, Lim T J. Beamforming with limited feedback in amplify-and-forward cooperative networks. IEEE GlobeCom, 2007:3457-3461.
[135] Burkhart M, Rickenbach P, Wattenhofer R, et al. Does topology control reduce interference. Proc ACM Int Symp on Mobile Ad-hoc Networking and Computing, 2004:9-19.
[136] Rickenbach P, Schmid S, Wattenhofer R, et al. A robust interference model for wireless ad-hoc networks. Proc IEEE Int Parallel and Distributed Processing Symp, 2005.
[137] Moaveni-Nejad K, Li X. Low interference topology control for wireless ad hoc networks. Ad Hoc and Sensor Wireless Networks, 2004.
[138] Johansson T, Carr-Motyckova L. Reducing interference in ad hoc networks through topology control. Workshop on Discrete Algo and Meth for Mobile Computing and Commun, 2005.
[139] Meyer F, Schindelhauer C, Volbert K, et al. Energy, congestion and dilation in radio networks. Proc of the 14th ACM Symp on Parallel Algorithm and Architecture, 2002.
[140] Narayanaswamy S, Kawadia V, Sreenivas R S, et al. Power control in ad-hoc networks: theory, architecture, algorithm and implementation of the COMPOW protocol. Proc of the European Wireless Conf, 2002:156-162.
[141] Kawadia V, Kumar P R. Principles and protocols for power control in ad hoc networks. IEEE J Selected Areas in Commun, 2005, 23(5):76-88.
[142] Agarwal S, Krishnamurthy S V, Katz R H, et al. Distributed power control in ad-hoc wireless networks. Personal Indoor Mobile Radio Conf, 2001.
[143] Li Q, Fan P Y, Wu D O. Energy efficient routing in ad hoc networks with Nakagami-m fading channels. IEEE ICC, 2009:1-6.
[144] Jenkac H, Mayer T, Stockhammer T, et al. Soft decoding of LT-codes for wireless broadcast. Proc IST Mobile Summit, 2005.
[145] Byers J, Luby M, Mitzenmacher M, et al. A digital fountain approach to reliable distribution of bulk data. Conf SIGCOMM, 1998:56-67.
[146] Luby M. LT codes. IEEE Symposium on Foundations of Computer Science, 2002.
[147] Shokrollahi A. Raptor codes. IEEE Int Symp on Inform Theory, 2004.
[148] Etasami O, Molkaraie M, Shokrollahi A. Raptor codes on symmetric channels. IEEE Int Symp on Inform Theory, 2004:38.
[149] Palanki R, Yedidia J. Rateless codes on noisiy channels. Proc. Int Symp on Inform Theory, 2004.
[150] Gallager R G. Low-density parity-check codes. IEEE Trans on Inform Theory, 1962, 8(1):21-28.
[151] Tanner R M. A recursive approach to low complexity codes. IEEE Trans on Inform Theory, 1981, 27(5):534-547.
[152] Morelos-Zaragoza R H. The art of error correcting coding. John Wiley & Sons, 2006.
[153] Chakrabarti A, Baynast A, Sabharwal A, et al. Low density parity check codes for the relay channel. IEEE J Selected Areas Commun, 2007, 25(2):280-291.
[154] Host-Madsen A, Zhang J. Capacity bounds and power allocation for the wireless relay channel. IEEE Trans on Inform Thoery, 2005, 51(6):2020-2040.
[155] Asmussen S. Applied Probability and Queues. Springer, 2003.
[156] McEliece R, Stark W. Channels with block interference. IEEE Trans on Inform. Theory, 1984, 30(1):44-53.