认知网络和LTE蜂窝网络中通信资源分配与功率控制算法的研究
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摘要
随着现在通信技术和社会科技的飞速发展,人们对于通信质量的要求越来越高。通信质量通常是由通信带宽、发射功率、编码调制方式、信道质量和通信环境决定的。在一个通信系统中如何给用户分配这些资源,包括带宽、发射功率、编码调制方式等,使得系统的数据传送率最大、服务质量最好成为现在通信研究的热门和关键部分。另一方面,通信电池设备的发展缓慢和现在生态环境的需求,如何在保证通信质量的情况,降低通信能量的消耗,达到能量有效的绿色通信,也是现在通信的关键问题。本文将从能量有效和频谱有效的角度去研究不同网络系统的资源分配和功率控制。
认知无线电技术的提出为了解决频谱资源使用不合理,从而提高频谱资源的利用率。它可以让认知用户在授权用户不使用频谱的时候,接入并使用频谱资源。本文将研究认知用户如何感知信道并且决定最优的传送时间和功率分配。在做优化时,本文考虑了能量有效性、吞吐量(传送速率)、和对授权用户的干扰。本文证明了在使用多个信道进行数据传送时,存在一个最优闭式解,并且给出了在每个信道上的最优功率分配方案。
协作网络技术是通过中继节点帮助源节点的通信来增加数据传送率,将协作网络技术应用于认知网络可以有效的提高认知用户系统的传送速率。本文在考虑频谱有效性的资源分配的同时,提出了一种在协作认知网络中中继节点选择和功率分配的最优方案,并且进一步提出一种简化的节点选择的次优方案。从仿真结果可以看出次优方案具有与最优方案相近的性能。
在蜂窝通信系统中,小区间的干扰是影响系统性能的主要因素,特别是小区频率复用因子为1的系统。LTE作为下一代高速无线宽带网络技术,对通信资源、调制编码方式、和功率分配等给出了一系列的限制条件。本文将研究在LTE通信系统中的资源分配,针对LTE上行系统的频谱资源和功率分配,提出了一种当小区频率复用因子为1时基于小区之间信息交互的资源分配方式来降低小区之间的干扰,从而提高小区边缘用户的频谱效率和小区用户的平均频谱效率。同时,本论文对LTE下行系统进行频谱有效和能量有效的资源分配进行了研究,研究表明采用能量有效的资源分配不仅能够保证系统的数据传送率,而且也降低了小区之间的干扰。
With the quick development of wireless communication technology and sharp increase in its applications, Quality-of-Service (QoS) in wireless systems is becoming very important. QoS of each user in a multiple access network depends on bandwidth, transmission power, coding and modulation, channel quality, etc. How to assign these resources to each user to optimize the throughput or QoS of the whole network is a critical issue for future wireless networks. On the other hand, the battery technology is unable to catch up with the sharply increasing capacity requirement in mobile devices. Consequently, energy-efficient wireless networks, also known as Green Radio, is becoming a more and more popular and critical research area, as evidenced by many workshops in international conferences, special issues of journals, and research groups in the world. Reducing energy consumption in wireless communications is also beneficial to environments and good for sustaining development. Therefore, this paper will focus on resource allocation for energy-efficient and spectral-efficient wireless networks in this dissertation.
To effectively improve spectral efficiency of wireless networks, cognitive radio (CR) has been proposed to use the licensed spectrum when the licensed users are not active spatially or temporally. In this dissertation, how a CR user senses available spectrum bands, selects the most appropriate one, and then optimizes transmission parameters will be studied. When determining transmission period and power, this dissertation also takes spectral efficiency, throughput, and interference limit to the licensed users into consideration. The dissertation proves that there is a closed-form solution for the duration of data transmission. A power allocation method for all the used channels is also proposed in the dissertation.
Cooperative relay technique can improve throughput and mitigate interference in wireless networks, which is an ideal technique for CR. This dissertation will apply this technique in CR networks to increase throughput of cognitive users and avoid interference to the licensed users. Since both relay node selection and power allocation relate to the spectral efficiency of CR networks, this dissertation first develops a joint relay selection and power allocation approach that maximizes the throughput of a CR network with cooperative relay. The dissertation then proposes a simplified approach that significantly reduces the complexity with only minor performance degradation. The simplified approach performs almost as well as the optimal method, which can be seen from the simulation results.
In cellular networks, inter-cell interference (ICI) significantly degrades performance, especially for a network with a unit frequency reuse factor. Long term evolution (LTE) is a standard for future cellular networks. In the LTE standard, many practical constraints are posted on frequency resource, coding and modulation, power allocation, etc. In the dissertation, a resource allocation and power assignment scheme for uplink transmission under the above practical constraints is developed. The dissertation also studies energy-efficient resource and power allocation for downlink transmission in LTE. Our research indicates that the energy-efficient design not only maintains reasonable high throughput but also effectively mitigates ICI by reducing transmission power.
认知无线电技术的提出为了解决频谱资源使用不合理,从而提高频谱资源的利用率。它可以让认知用户在授权用户不使用频谱的时候,接入并使用频谱资源。本文将研究认知用户如何感知信道并且决定最优的传送时间和功率分配。在做优化时,本文考虑了能量有效性、吞吐量(传送速率)、和对授权用户的干扰。本文证明了在使用多个信道进行数据传送时,存在一个最优闭式解,并且给出了在每个信道上的最优功率分配方案。
协作网络技术是通过中继节点帮助源节点的通信来增加数据传送率,将协作网络技术应用于认知网络可以有效的提高认知用户系统的传送速率。本文在考虑频谱有效性的资源分配的同时,提出了一种在协作认知网络中中继节点选择和功率分配的最优方案,并且进一步提出一种简化的节点选择的次优方案。从仿真结果可以看出次优方案具有与最优方案相近的性能。
在蜂窝通信系统中,小区间的干扰是影响系统性能的主要因素,特别是小区频率复用因子为1的系统。LTE作为下一代高速无线宽带网络技术,对通信资源、调制编码方式、和功率分配等给出了一系列的限制条件。本文将研究在LTE通信系统中的资源分配,针对LTE上行系统的频谱资源和功率分配,提出了一种当小区频率复用因子为1时基于小区之间信息交互的资源分配方式来降低小区之间的干扰,从而提高小区边缘用户的频谱效率和小区用户的平均频谱效率。同时,本论文对LTE下行系统进行频谱有效和能量有效的资源分配进行了研究,研究表明采用能量有效的资源分配不仅能够保证系统的数据传送率,而且也降低了小区之间的干扰。
With the quick development of wireless communication technology and sharp increase in its applications, Quality-of-Service (QoS) in wireless systems is becoming very important. QoS of each user in a multiple access network depends on bandwidth, transmission power, coding and modulation, channel quality, etc. How to assign these resources to each user to optimize the throughput or QoS of the whole network is a critical issue for future wireless networks. On the other hand, the battery technology is unable to catch up with the sharply increasing capacity requirement in mobile devices. Consequently, energy-efficient wireless networks, also known as Green Radio, is becoming a more and more popular and critical research area, as evidenced by many workshops in international conferences, special issues of journals, and research groups in the world. Reducing energy consumption in wireless communications is also beneficial to environments and good for sustaining development. Therefore, this paper will focus on resource allocation for energy-efficient and spectral-efficient wireless networks in this dissertation.
To effectively improve spectral efficiency of wireless networks, cognitive radio (CR) has been proposed to use the licensed spectrum when the licensed users are not active spatially or temporally. In this dissertation, how a CR user senses available spectrum bands, selects the most appropriate one, and then optimizes transmission parameters will be studied. When determining transmission period and power, this dissertation also takes spectral efficiency, throughput, and interference limit to the licensed users into consideration. The dissertation proves that there is a closed-form solution for the duration of data transmission. A power allocation method for all the used channels is also proposed in the dissertation.
Cooperative relay technique can improve throughput and mitigate interference in wireless networks, which is an ideal technique for CR. This dissertation will apply this technique in CR networks to increase throughput of cognitive users and avoid interference to the licensed users. Since both relay node selection and power allocation relate to the spectral efficiency of CR networks, this dissertation first develops a joint relay selection and power allocation approach that maximizes the throughput of a CR network with cooperative relay. The dissertation then proposes a simplified approach that significantly reduces the complexity with only minor performance degradation. The simplified approach performs almost as well as the optimal method, which can be seen from the simulation results.
In cellular networks, inter-cell interference (ICI) significantly degrades performance, especially for a network with a unit frequency reuse factor. Long term evolution (LTE) is a standard for future cellular networks. In the LTE standard, many practical constraints are posted on frequency resource, coding and modulation, power allocation, etc. In the dissertation, a resource allocation and power assignment scheme for uplink transmission under the above practical constraints is developed. The dissertation also studies energy-efficient resource and power allocation for downlink transmission in LTE. Our research indicates that the energy-efficient design not only maintains reasonable high throughput but also effectively mitigates ICI by reducing transmission power.
引文
[1] M. Pedram. Power optimization and management in embedded systems. Proc. ASP-DAC 2001, (Yokohama, Japan), pp. 239–244, Feb. 2001
[2] L. Benini, A. Bogliolo, and G. De Micheli. A survey of design techniques for system-level dynamic power management. IEEE Trans. VLSI Syst., vol. 8, pp. 299–316, June 2000
[3] A. Raghunathan, N. Jha, and S. Dey. High-level power analysis and optimization. Norwell, MA: Kluwer Academic Publishers, 1998
[4] C. Schurgers. Energy-aware wireless communications. PhD thesis, University of California Los Angeles, 2002
[5] N. Jindal, S. Weber, and J. G. Andrews. Fractional power control for decentralized wireless networks. IEEE Trans. Wireless Commun. vol. 7, no. 12, pp. 5482-5492, Dec. 2008
[6] L. Feeney. Energy-efficient communication in AD HOC wireless networks. Book chapter of Mobile Ad Hoc Networking, 2004
[7] FCC. Spectrum policy task force report. ET Docket 02-155, Nov. 2002
[8] Unlicensed operations in the TV broadcast bands, second memorandum opinion and order, FCC, 10-174, Sept. 2010
[9] S. Haykin. Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun., pp. 201–220, Feb. 2005
[10] S. Stotas and A. Nallanathan. Optimal sensing time and power allocation in multiband cognitive radio networks. IEEE Trans. Commun.,vol. 51, pp. 226–235, Jan. 2011
[11] J. Ma, G. Y. Li, and B. H. Juang. Signal processing in cognitive radio. Proc. IEEE, vol. 97, no. 5, pp. 805-823, May 2009
[12] X. Zhou, G. Y. Li, D. Li, D. Wang, et al.. Probabilistic resource allocation for opportunistic spectrum access. IEEE Trans. Wireless Commun., vol. 9, no. 9, pp. 2870-2879, Sept. 2010
[13] X. Zhou, J. Ma, G. Y. Li, et al.. Probability-based optimization of inter-sensing duration and power control in cognitive radio. IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 4922-4927, Oct. 2009
[14] Y. Zhang and C. Leung. Resource allocation in an OFDM-based cognitive radio system. IEEE Trans. Commun., vol. 57, no. 7, pp. 1928-1931, July 2009
[15] Y. Zhang and C. Leung. Cross-layer resource allocation for mixed services in multiuser OFDM-based cognitive radio systems. IEEE Trans. Veh. Tech., vol. 58, no. 8, pp. 4605- 4619, Oct. 2009
[16] F. Cao and Z. Fan. The tradeoff between energy efficiency and system performance of femtocell deployment. Proc. IEEE 2010 7th Int. Symp. on Wireless Commun. Systems, Sept. 2010
[17] J. Gambini and U. Spagnolini. Wireless over cable for energy-efficient femtocell systems. IEEE Globecom Workshops, Dec. 2010
[18] U. C. Kozat, I. Koutsopoulos, and L. Tassiulas. Cross-layer design for power efficiency and QoS provisioning in multi-hop wireless networks. IEEE Trans. Wireless Commun., vol. 5, pp. 3306–3315, Nov. 2006
[19] P. Pham, S. Perreau, and A. Jayasuriya. New cross-layer design approach to adhoc networks under rayleigh fading. IEEE J. Sel. Areas Commun., vol. 23, pp. 28–39, Jan. 2005
[20] M. A. Haleem and R. Chandramouli. Adaptive downlink scheduling and rate selection: a cross-layer design. IEEE J. Sel. Areas Commun., vol. 23, pp. 1287–1297, Jan. 2005
[21] L. Thiele, M. Schellmann, and T. Wirth, et al.. Interference-Aware Scheduling in the synchronous cellular multi-antenna downlink. Proc. IEEE Veh. Tech. Conf. (VTC’09), Spring 2009
[22] Y. Xiang, J. Luo, and C. Hartmann. Inter-cell interference mitigation through flexible resource reuse in OFDMA based Communication Networks. European Wireless 2007
[23] X. Mao, A. Maaref, and K. Teo. Adaptive soft frequency reuse for inter-cell interference coordination in SC-FDMA based 3GPP LTE uplink. Proc. of IEEE GLOBECOM 2008, Nov. 2008, pp. 1–6
[24] I. C. Wong, O. Oteri, and W. McCoy. Optimal resource allocation in uplink SC-FDMA systems. IEEE Trans. Wireless Commu., vol.8, no.5, pp. 2161–2165, May 2009
[25] P. Svedman. Cross-layer aspects in OFDMA scheduling. PhD dissertation, June 2007
[26] Y.-C. Liang, R. Zhang and J.M. Cioffi. Transmit optimization for MIMO-OFDM with delay-constrained and no-delay-constrained traffic. IEEE Trans. Signal Processing, Vol. 54, Issue 8, pp. 3190– 3199, Aug. 2006
[27] D. Liao, L. Li, and S. Xu, et al.. Opportunistic scheduling with multiple QoS constraints in wireless multiservice networks. Proc. IEEE WCNC, 2007, March 2007
[28] N. Zorba and A. Pérez-Neira. Robust multi-beam opportunistic schemes under quality of service constraints. Proc. ICC, 2007, May 2007
[29] N. Zorba and A. Pérez-Neira. Optimum number of beams in multiuser opportunistic schemes under QoS constraints. Proc. International ITG/IEEE Workshop on Smart Antennas TechGate, Feb. 2007
[30] P. Pischella and J.C. Belore, Power Control in Distributed Cooperative OFDMA Cellular Networks, IEEE Trans. Wireless Commun., vol. 7, no. 5, pp. 1900-1905, May. 2008.
[31] C. Castellanos et al., Performance of Uplink Fractional Power Control in UTRAN LTE, pp. 2517-2521, VTC Spring 2008, Singapore.
[32] L. Venturino, N. Prasad, and X. Wang, Coordinated Scheduling and Power Allocation in Downlink Multicell OFDMA Networks, IEEE Trans. on Vehicular Technology, vol. 58, no. 7, pp. 2835-2848, 2009.
[33] W. Xiao, R. Ratasuk, and A. Ghosh, et al.. Uplink Power Control, Interference Coordination and Resource Allocation for 3GPP E-UTRA. IEEE Transactions on Vehicular Technology, September 2006.
[34] A. M. Rao. Reverse Link Power Control for Managing Inter-cell Interference in Orthogonal Multiple Access Systems. IEEE Transactions on Vehicular Technology, October
[35] T. Michel and G. Wunder. Achieving QoS and efficiency in the MIMO downlink with limited power. Proc. International ITG/IEEE Workshop on Smart Antennas Tech Gate, Feb. 2007
[36] D. Liao, L. Li, S. Xu, et al.. Traffic aided opportunistic scheduling with QoS support for multiservice CDMA uplink. Proc. IEEE WCNC, 2007, March 2007
[37] R. Iyengar, et al.. Delay analysis of 802.16 based last mile wireless networks. Proc. IEEE Globecom , 2005 , Nov. 2005
[38] D. Niyato, et al.. Queue-aware uplink bandwidth allocation for polling services in 802.16 broadband wireless networks. Proc. IEEE Globecom., 2005, Nov. 2005
[39] D. Rajan , A. Sabharwal and B. Aazhang. Delay-bounded packet scheduling of bursty traffic over wireless channels. IEEE Trans. Information Theory , Vol. 50 , Issue 1 , pp. 125– 144 , Jan. 2004
[40] D. Niyato and E. Hossain. Queueing analysis of OFDM/ TDMA systems. Proc. IEEE Globecom, 2005, Nov. 2005
[41] G. Song, Y. Li, L.J. Cimini et al.. Joint channel aware and queue-aware data scheduling in multiple shared wireless channels. Proc. IEEE WCNC, 2004
[42] D. Wu and R. Negi. Effective capacity: a wireless link model for support of QoS. IEEE Trans. Wireless Comm., Vol. 2, Issue 4, July 2003
[43] Draft IEEE std 802.16e/D9. IEEE standard for local and metropolitan area networks part 16: air interface for fixed and mobile broadband wireless access systems. June 2005
[44] G. L. St¨uber. Principles of mobile communication. Norwell, MA: Kluwer Academic Publishers, 2001
[45] R. G. Gallager. Information theory and reliable communication. John Wiley & Sons, Inc., 1968
[46] Y. (G.) Li and G. L. St¨uber. OFDM for Wireless Communications. Springer, 2006
[47] S. Sampei, S. Komaki, S., and N. Morinaga. Adaptive modulation/TDMA scheme for personal multimedia communication systems. Proc. IEEE GLOBECOM 1994, pp. 989–993, Nov. 1994
[48] M. Ouchi, H. J. Lee, S. Komaki, et al.. Proposal for modulation level controlled radio system applied to ATM networks. Proc. of Fourth European Conference on Radio Relay Systems, pp. 322–327, Oct. 1993
[49] R. G. Gallager. Power limited channels: Coding, multiaccess, and spread spectrum. Proc. Conf. Inform. Sci. and Syst., vol. 1, Mar. 1988
[50] S. Verdu. On channel capacity per unit cost. IEEE Trans. Inf. Theory., vol. 36, pp. 1019–1030, Sept. 1990
[51] S. Verdu. Spectral efficiency in the wideband regime. IEEE Trans. Inf. Theory., vol. 48, pp. 1319–1343, June 2002
[52] F. Meshkati, H. V. Poor, S. C. Schwartz, et al.. An energy-efficient approach to power control and receiver design in wireless networks. IEEE Trans. Commun., vol. 5, pp. 3306–3315, Nov. 2006
[53] A. Y. Wang, S. Cho, C. G. Sodini, et al.. Energy efficient modulation and MAC for asymmetric RF microsensor system. Int. Symp. Low Power Electronics and Design, (Huntington Beach, CA), pp. 106–111, 2001
[54] S. Cui, A. J. Goldsmith, and A. Bahai. Energy-constrained modulation optimization. IEEE Trans. Wireless Commun., vol. 4, pp. 2349–2360, Sept. 2005
[55] G. Miao, N. Himayat, Y. Li, and D. Bormann. Energy-efficient design in wireless OFDMA. Proc. IEEE ICC 2008, pp. 3307–3312, May 2008
[56] C. Schurgers and M. B. Srivastava. Energy optimal scheduling under average throughput constraint communications. Proc. IEEE ICC 2003, vol. 3, pp. 1648–1652, 2003
[57] S. Cui, A. Goldsmith, and A. Bahai. Joint modulation and multiple access optimization under energy constraints. Proc. IEEE GLOBECOM 2004, vol. 1, pp. 151–155, Nov. 2004
[58] R. Mangharam, R. Rajkumar, S. Pollin, et al.. Optimal fixed and scalable energy management for wireless networks. Proc. IEEE INFOCOM 2005, vol. 1, pp. 114–125, Mar. 2005
[59] S. Cui, A. Goldsmith, and A. Bahai. Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks. IEEE J. Sel. Areas Commun., vol. 22, pp. 1089–1098, Aug. 2004
[60] S. K. Jayaweera. An energy-efficient virtual MIMO architecture based on VBLAST processing for distributed wireless sensor networks. Proc. IEEE SECON 2004, pp. 299–308, Oct. 2004
[61] J. Rabaey, J. Ammer, J. L. da et al.. PicoRadio: Ad-hoc wireless networking of ubiquitous low-energy sensor/monitor nodes. IEEE VLSI, pp. 9–12, 2000
[62] M. Haenggi and D. Puccinelli. Routing in ad hoc networks: a case for long hops. IEEE Commun. Magazine, vol. 43, pp. 112–119, Oct. 2005
[63] R. Knopp and P.A. Humblet. Information capacity and power control in single-cell multiuser communications. Proc. IEEE ICC. , June 1995
[64] G. B. Giannakis, Y. Hua, P. Stoica et al.. Signal processing advances in wireless and mobile communications: trends in single- and multi-user systems, Prentice Hall PTR, 2001
[65] C. Comaniciu, N.B. Mandayam, and H.V. Poor. Wireless networks: multiuser detection in cross-layer design. Springer, 2005
[66] W. L. Huang and K. B. Letaief. Cross-layer scheduling and power control combined with adaptive modulation for wireless ad-hoc networks. IEEE Trans. Comm , Vol. 55 , Issue 4, pp. 728– 739 , April 2007
[67] J. Lee , R.V. Sonalkar and J.M. Cioffi. Multiuser bit loading for multicarrier systems. IEEETrans. Comm., Vol. 54, Issue 7, pp. 1170– 1174, July 2006
[68] L. Georgiadis, M.J. Neely and L. Tassiulas. Resource Allocation and Cross Layer Control in Wireless Networks. Now Publishers Inc., 2006
[69] I. Mitola, J. Maguire. Cognitive radio: making software radios more personal. IEEE Personal Communications 1999, vol.6 no.4, pp 13-18
[70] D. Cabric, S. Mishra, and R. W. Brodersen. Implementation issues in spectrum sensing for cognitive radios. Proc. IEEE Asil. Conf. signals, Sys., and Comp., (ACSSC 2004)
[71] FCC. ET Docket No. 03-322. Notice of proposed rule making and order. December 2003
[72] I. F. Akyildiz, W.-Y Lee, M. C. Vuran, et al.. A survey on spectrum management in cognitive radio networks. IEEE Commun. Mag., pp. 40–48, April 2008
[73] 3GPP TS 36.300 V9.0.0. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (E-UTRAN); overall description; Release 9. June 2009
[74] X. Zhou, G. Y. Li, and Y. H. Kwon, et al.. Detection timing and channel selection for periodic spectrum sensing in cognitive radio. Proc. IEEE Global Telecommun Conf., Dec. 2008
[75] A. Hoang and Y.-C. Liang. Adaptive scheduling of spectrum sensing periods in cognitive radio networks. Proc. IEEE Global Telecommun. Conf., Nov. 2007, pp. 3128–3132
[76] Y. Pei, A. Hoang, and Y-C. Liang. Sensing-throughput tradeoff in cognitive radio networks: how frequently should spectrum sensing be carried out?. Proc. Personal, Indoor and Mobile Radio Commun., Sept. 2007, pp. 1–5
[77] P. Wang, M. Zhao, and L. Xiao, et al.. Power allocation in OFDM-based cognitive radio systems. Proc. IEEE Global Telecommun. Conf., Nov. 2007, pp. 4061–4065
[78] G. Miao, N. Himayat, and G. Y. Li. Energy-efficient transmission in frequency-selective channels. Proc. IEEE Global Telecommun. Conf., Dec. 2008
[79] G. Ganesan and G. Y. Li. Cooperative spectrum sensing in cognitive radio - part I: two user networks. IEEE Trans.Commun., vol. 6, no. 6, pp. 2204–2213, June 2007
[80] G. Ganesan and G. Y. Li. Cooperative spectrum sensing in cognitive radio - part II: multiuser networks. IEEE Trans. Commun., vol. 6, no.6, pp. 2214–2222, June 2007
[81] J. Jia, J. Zhang, and Q. Zhang. Cooperative relay for cognitive radio networks. in Proc. IEEE INFOCOM, Apr. 2009, pp. 2304–2312
[82] R. Kwan, C. Leung, and J. Zhang. Resource allocation in an LTE cellular communication system. Proc. IEEE Int. Conf. Commun., Dresden, German, pp. 1-5, June 2009
[83] A. Bletsas, A. Khisti, and D. P. Reed, et al.. A simple cooperative diversity method based on network path selection. IEEE Sel. Areas Commun., vol. 24, no. 3, pp. 659–672, Mar. 2006
[84] X. Zhou, J. Ma, and G. Y. Li, et al.. Probability-based optimization of inter-sensing duration and power control in cognitive radio. IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 4922–4927, Oct. 2009
[85] A. Bletsas, A. Khisti, and D. P. Reed, et al.. A simple cooperative diversity method based on network path selection. IEEE Sel. Areas Commun., vol. 24, no. 3, pp. 659–672, Mar. 2006
[86] K. J. R. Liu, A. K. Sadek, and W. Su, et al.. Cooperative communications and networking. Cambridge University Press, 2009
[87] J. Mietzner, L. Lampe, and R. Schober. Distributed transmit power allocation for multihop cognitive-radio systems. IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 5187–5201, Oct. 2009
[88] H. G. Myung, J. Lim, and David J. Goodman. Single carrier FDMA for uplink wireless transmission. IEEE Veh. Tech. Mag., vol.1, no.3, pp. 30–38, 2006
[89] R1-050507. Soft frequency reuse scheme for UTRAN LTE. Huawei. 3GPP TSG RAN WG1 Meeting. Athens, Greece, May 2005
[90] X. Mao, A. Maaref, and K. Teo. Adaptive soft frequency reuse for intercell interference coordination in SC-FDMA based 3GPP LTE uplink. Proc. of IEEE GLOBECOM 2008, Nov. 2008, pp. 1–6
[91] I. C. Wong, O. Oteri, and W. McCoy. Optimal resource allocation in uplink SC-FDMA systems. IEEE Trans. Wireless Commu., vol.8, no.5, pp. 2161–2165, May 2009
[92] X. Qiu and K. Chawla. On the performance of adaptive modulation in cellular systems. IEEE Trans. Commu., vol. 47, no.6, pp. 884–895, June. 1999
[93] 3GPP TS 36.213 V9.0.0. Evolved universal terrestrial radio access (EUTRA); physical layer procedures; Release 9. Dec. 2009
[94] R. Giuliano and F. Mazzenga. Exponential effective SINR approximations for OFDM/OFDMA based cellular system planning. IEEE Trans. Wireless Commu., vol.8, no.9, pp. 4434–4439, 2009
[95] S. Lee, I. Pefkianakis, and A. Meyerson, et al.. Proportional fair frequency-domain packet scheduling for 3GPP LTE uplink. Proc. of IEEE INFOCOM, Apr. 2009
[96] Y. Chen, S.-Q. Zhang, and S.-G. Xu, et al.. Fundamental tradeoffs on green wireless networks. To appear on IEEE Commun.Mag
[97] G. Y. Li, Z.-K. Xu, and C. Xiong, et al.. Energy-efficient wireless communications: tutorial, survey, and open issues. To appear on IEEE Wireless Commun. Mag
[98] G.-W. Miao, N. Himayat, and G. Y. Li, et al.. Distributed interference-aware energy-efficient power optimization. To appear on IEEE Trans. Wireless Commun
[99] J.-C. Fan, Q.-Y. Yin, and G. Y. Li, et al.. Adaptive block-level resource allocation in OFDMA networks. Submited to IEEE 2011 Int’l Conf. Comput. Commun. Networks, Maui, Hawaii, July-August, 2011
[100] L.-Y. Li, G. Wu, and H.-B. Xu, et al.. Joint Power Control and Resource Allocation for Interference Mitigation in LTE Uplink Systems. To appear in the 45th Conf. Inf. Sci. and Sys., Baltimore, MD, March 2011
[101] M. McHenry, E. Livsucs, T. Nguyen, et al.. XG dynamic spectrum access field test results. IEEE Commun. Mag., 2007, vol.45 no. 6, pp 51-517
[102] P. D. Stran. Game theory and strategy. Mathematical Association of America, 1993
[103] A. J. Goldsmith and P. P. Varaiya. Capacity of fading channels with channel side information. IEEE Trans. Inf. Theory., vol. 43, pp. 1986–1992, July 1997
[104] J. Jang and K. B. Lee. Transmit power adaptation for multiuser OFDM systems. IEEE J. Sel. Areas Commun., vol. 21, pp. 171–178, Feb. 2003
[105] R. J. McEliece and W. E. Stark. Channels with block interference. IEEE Trans. Inf. Theory., vol. 30, pp. 44–53, Jan. 1984
[106] A. Goldsmith. Wireless Communications. Cambridge University Press, 2005
[107] M. Hellebrandt, R. Mathar, and M. Scheibenbogen. Estimating position and velocity of mobiles in a cellular radio network. IEEE Trans. Veh. Tech., vol. 46
[108] G. Sun, J. Chen, W. Guo, et al.. Signal processing techniques in network aided positioning: a survey of state-of-the-art positioning designs. IEEE Sig. Processing Mag., vol. 22
[109] M. Pischella and J.-C. Belfiore. Power control in distributed cooperative OFDMA cellular networks. vol. 7, pp. 1900–1906, May 2008
[110] A. Kumar, D. Manjunath, and J. Kuri. Wireless Networking. Morgan Kaufmann, 2008
[111] D. Tse and P Viswanath. Fundamentals of wireless communication. Cambridge University Press, 2005
[112] C. E. Shannon. Communication in the presence of noise. Proc. IRE, vol. 37, pp. 10–21, Jan. 1949
[113] N. Feng, S. C. Mau, and N. B. Mandayam. Pricing and power control for joint network-centric and user-centric radio resource management. IEEE Trans. Commun., vol. 52, pp. 1547–1557, Sept. 2004
[114] B. Prabhakar, E. U. Biyikoglu, and A. E. Gamal. Energy-efficient transmission over a wireless link via lazy packet scheduling. Proc. IEEE Infocom 2001, vol. 1, pp. 386–394, Apr. 2001
[115] S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004
[116] K. C. Kiwiel and K. Murty. Convergence of the steepest descent method for minimizing quasiconvex functions. J. of Optimization Theory and Applications, vol. 89, pp. 221–226, Sept. 2005
[117] G. Miao, N. Himayat, and Y. Li. Energy-efficient transmission in frequency selective channels. Proc. IEEE Globecom 2008, pp. 1–5, Dec. 2008
[118] D. Fudenberg and J. Tirole. Game Theory. Cambridge, MA: MIT Press, 1991
[119] R. D. Yates. A framework for uplink power control in cellular radio systems. pp. 1341–1347, Sept. 1995
[120] S. M. Ross. Stochastic Process. John Wiley & Sons, Inc., 1996
[121] K. Feher. Advanced Digital Communications. Englewood Cliffis, NJ: Prentice-Hall, 1987
[122] Y. (G.) Li and G. L. St¨uber. OFDM for Wireless Communications. Springer, 2006
[123] H. Dai, A. F. Molisch, and H. V. Poor. Downlink capacity of interference-limited MIMO systems with joint detection. IEEE Trans. Wireless Commun., vol. 3, pp. 442–453, Mar. 2004
[124] S. Shamai and B. M. Zaidel. Enhancing the cellular downlink capacity via coprocessing at the transmitting end. Proc. Conf. Veh. Tech. Spring, 2005, vol. 3, pp. 1745–1749, 2001
[125] 3GPP TS 36.300 V9.0.0. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (EUTRAN); overall description; Release 9. June 2009
[126] K. B. Letaief and Y. J. Zhang. Dynamic multiuser resource allocation and adaptation for wireless systems. IEEE Wireless Comm., Special issue on Smart Antennas, Vol. 13, Issue 4, Aug. 2006
[2] L. Benini, A. Bogliolo, and G. De Micheli. A survey of design techniques for system-level dynamic power management. IEEE Trans. VLSI Syst., vol. 8, pp. 299–316, June 2000
[3] A. Raghunathan, N. Jha, and S. Dey. High-level power analysis and optimization. Norwell, MA: Kluwer Academic Publishers, 1998
[4] C. Schurgers. Energy-aware wireless communications. PhD thesis, University of California Los Angeles, 2002
[5] N. Jindal, S. Weber, and J. G. Andrews. Fractional power control for decentralized wireless networks. IEEE Trans. Wireless Commun. vol. 7, no. 12, pp. 5482-5492, Dec. 2008
[6] L. Feeney. Energy-efficient communication in AD HOC wireless networks. Book chapter of Mobile Ad Hoc Networking, 2004
[7] FCC. Spectrum policy task force report. ET Docket 02-155, Nov. 2002
[8] Unlicensed operations in the TV broadcast bands, second memorandum opinion and order, FCC, 10-174, Sept. 2010
[9] S. Haykin. Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun., pp. 201–220, Feb. 2005
[10] S. Stotas and A. Nallanathan. Optimal sensing time and power allocation in multiband cognitive radio networks. IEEE Trans. Commun.,vol. 51, pp. 226–235, Jan. 2011
[11] J. Ma, G. Y. Li, and B. H. Juang. Signal processing in cognitive radio. Proc. IEEE, vol. 97, no. 5, pp. 805-823, May 2009
[12] X. Zhou, G. Y. Li, D. Li, D. Wang, et al.. Probabilistic resource allocation for opportunistic spectrum access. IEEE Trans. Wireless Commun., vol. 9, no. 9, pp. 2870-2879, Sept. 2010
[13] X. Zhou, J. Ma, G. Y. Li, et al.. Probability-based optimization of inter-sensing duration and power control in cognitive radio. IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 4922-4927, Oct. 2009
[14] Y. Zhang and C. Leung. Resource allocation in an OFDM-based cognitive radio system. IEEE Trans. Commun., vol. 57, no. 7, pp. 1928-1931, July 2009
[15] Y. Zhang and C. Leung. Cross-layer resource allocation for mixed services in multiuser OFDM-based cognitive radio systems. IEEE Trans. Veh. Tech., vol. 58, no. 8, pp. 4605- 4619, Oct. 2009
[16] F. Cao and Z. Fan. The tradeoff between energy efficiency and system performance of femtocell deployment. Proc. IEEE 2010 7th Int. Symp. on Wireless Commun. Systems, Sept. 2010
[17] J. Gambini and U. Spagnolini. Wireless over cable for energy-efficient femtocell systems. IEEE Globecom Workshops, Dec. 2010
[18] U. C. Kozat, I. Koutsopoulos, and L. Tassiulas. Cross-layer design for power efficiency and QoS provisioning in multi-hop wireless networks. IEEE Trans. Wireless Commun., vol. 5, pp. 3306–3315, Nov. 2006
[19] P. Pham, S. Perreau, and A. Jayasuriya. New cross-layer design approach to adhoc networks under rayleigh fading. IEEE J. Sel. Areas Commun., vol. 23, pp. 28–39, Jan. 2005
[20] M. A. Haleem and R. Chandramouli. Adaptive downlink scheduling and rate selection: a cross-layer design. IEEE J. Sel. Areas Commun., vol. 23, pp. 1287–1297, Jan. 2005
[21] L. Thiele, M. Schellmann, and T. Wirth, et al.. Interference-Aware Scheduling in the synchronous cellular multi-antenna downlink. Proc. IEEE Veh. Tech. Conf. (VTC’09), Spring 2009
[22] Y. Xiang, J. Luo, and C. Hartmann. Inter-cell interference mitigation through flexible resource reuse in OFDMA based Communication Networks. European Wireless 2007
[23] X. Mao, A. Maaref, and K. Teo. Adaptive soft frequency reuse for inter-cell interference coordination in SC-FDMA based 3GPP LTE uplink. Proc. of IEEE GLOBECOM 2008, Nov. 2008, pp. 1–6
[24] I. C. Wong, O. Oteri, and W. McCoy. Optimal resource allocation in uplink SC-FDMA systems. IEEE Trans. Wireless Commu., vol.8, no.5, pp. 2161–2165, May 2009
[25] P. Svedman. Cross-layer aspects in OFDMA scheduling. PhD dissertation, June 2007
[26] Y.-C. Liang, R. Zhang and J.M. Cioffi. Transmit optimization for MIMO-OFDM with delay-constrained and no-delay-constrained traffic. IEEE Trans. Signal Processing, Vol. 54, Issue 8, pp. 3190– 3199, Aug. 2006
[27] D. Liao, L. Li, and S. Xu, et al.. Opportunistic scheduling with multiple QoS constraints in wireless multiservice networks. Proc. IEEE WCNC, 2007, March 2007
[28] N. Zorba and A. Pérez-Neira. Robust multi-beam opportunistic schemes under quality of service constraints. Proc. ICC, 2007, May 2007
[29] N. Zorba and A. Pérez-Neira. Optimum number of beams in multiuser opportunistic schemes under QoS constraints. Proc. International ITG/IEEE Workshop on Smart Antennas TechGate, Feb. 2007
[30] P. Pischella and J.C. Belore, Power Control in Distributed Cooperative OFDMA Cellular Networks, IEEE Trans. Wireless Commun., vol. 7, no. 5, pp. 1900-1905, May. 2008.
[31] C. Castellanos et al., Performance of Uplink Fractional Power Control in UTRAN LTE, pp. 2517-2521, VTC Spring 2008, Singapore.
[32] L. Venturino, N. Prasad, and X. Wang, Coordinated Scheduling and Power Allocation in Downlink Multicell OFDMA Networks, IEEE Trans. on Vehicular Technology, vol. 58, no. 7, pp. 2835-2848, 2009.
[33] W. Xiao, R. Ratasuk, and A. Ghosh, et al.. Uplink Power Control, Interference Coordination and Resource Allocation for 3GPP E-UTRA. IEEE Transactions on Vehicular Technology, September 2006.
[34] A. M. Rao. Reverse Link Power Control for Managing Inter-cell Interference in Orthogonal Multiple Access Systems. IEEE Transactions on Vehicular Technology, October
[35] T. Michel and G. Wunder. Achieving QoS and efficiency in the MIMO downlink with limited power. Proc. International ITG/IEEE Workshop on Smart Antennas Tech Gate, Feb. 2007
[36] D. Liao, L. Li, S. Xu, et al.. Traffic aided opportunistic scheduling with QoS support for multiservice CDMA uplink. Proc. IEEE WCNC, 2007, March 2007
[37] R. Iyengar, et al.. Delay analysis of 802.16 based last mile wireless networks. Proc. IEEE Globecom , 2005 , Nov. 2005
[38] D. Niyato, et al.. Queue-aware uplink bandwidth allocation for polling services in 802.16 broadband wireless networks. Proc. IEEE Globecom., 2005, Nov. 2005
[39] D. Rajan , A. Sabharwal and B. Aazhang. Delay-bounded packet scheduling of bursty traffic over wireless channels. IEEE Trans. Information Theory , Vol. 50 , Issue 1 , pp. 125– 144 , Jan. 2004
[40] D. Niyato and E. Hossain. Queueing analysis of OFDM/ TDMA systems. Proc. IEEE Globecom, 2005, Nov. 2005
[41] G. Song, Y. Li, L.J. Cimini et al.. Joint channel aware and queue-aware data scheduling in multiple shared wireless channels. Proc. IEEE WCNC, 2004
[42] D. Wu and R. Negi. Effective capacity: a wireless link model for support of QoS. IEEE Trans. Wireless Comm., Vol. 2, Issue 4, July 2003
[43] Draft IEEE std 802.16e/D9. IEEE standard for local and metropolitan area networks part 16: air interface for fixed and mobile broadband wireless access systems. June 2005
[44] G. L. St¨uber. Principles of mobile communication. Norwell, MA: Kluwer Academic Publishers, 2001
[45] R. G. Gallager. Information theory and reliable communication. John Wiley & Sons, Inc., 1968
[46] Y. (G.) Li and G. L. St¨uber. OFDM for Wireless Communications. Springer, 2006
[47] S. Sampei, S. Komaki, S., and N. Morinaga. Adaptive modulation/TDMA scheme for personal multimedia communication systems. Proc. IEEE GLOBECOM 1994, pp. 989–993, Nov. 1994
[48] M. Ouchi, H. J. Lee, S. Komaki, et al.. Proposal for modulation level controlled radio system applied to ATM networks. Proc. of Fourth European Conference on Radio Relay Systems, pp. 322–327, Oct. 1993
[49] R. G. Gallager. Power limited channels: Coding, multiaccess, and spread spectrum. Proc. Conf. Inform. Sci. and Syst., vol. 1, Mar. 1988
[50] S. Verdu. On channel capacity per unit cost. IEEE Trans. Inf. Theory., vol. 36, pp. 1019–1030, Sept. 1990
[51] S. Verdu. Spectral efficiency in the wideband regime. IEEE Trans. Inf. Theory., vol. 48, pp. 1319–1343, June 2002
[52] F. Meshkati, H. V. Poor, S. C. Schwartz, et al.. An energy-efficient approach to power control and receiver design in wireless networks. IEEE Trans. Commun., vol. 5, pp. 3306–3315, Nov. 2006
[53] A. Y. Wang, S. Cho, C. G. Sodini, et al.. Energy efficient modulation and MAC for asymmetric RF microsensor system. Int. Symp. Low Power Electronics and Design, (Huntington Beach, CA), pp. 106–111, 2001
[54] S. Cui, A. J. Goldsmith, and A. Bahai. Energy-constrained modulation optimization. IEEE Trans. Wireless Commun., vol. 4, pp. 2349–2360, Sept. 2005
[55] G. Miao, N. Himayat, Y. Li, and D. Bormann. Energy-efficient design in wireless OFDMA. Proc. IEEE ICC 2008, pp. 3307–3312, May 2008
[56] C. Schurgers and M. B. Srivastava. Energy optimal scheduling under average throughput constraint communications. Proc. IEEE ICC 2003, vol. 3, pp. 1648–1652, 2003
[57] S. Cui, A. Goldsmith, and A. Bahai. Joint modulation and multiple access optimization under energy constraints. Proc. IEEE GLOBECOM 2004, vol. 1, pp. 151–155, Nov. 2004
[58] R. Mangharam, R. Rajkumar, S. Pollin, et al.. Optimal fixed and scalable energy management for wireless networks. Proc. IEEE INFOCOM 2005, vol. 1, pp. 114–125, Mar. 2005
[59] S. Cui, A. Goldsmith, and A. Bahai. Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks. IEEE J. Sel. Areas Commun., vol. 22, pp. 1089–1098, Aug. 2004
[60] S. K. Jayaweera. An energy-efficient virtual MIMO architecture based on VBLAST processing for distributed wireless sensor networks. Proc. IEEE SECON 2004, pp. 299–308, Oct. 2004
[61] J. Rabaey, J. Ammer, J. L. da et al.. PicoRadio: Ad-hoc wireless networking of ubiquitous low-energy sensor/monitor nodes. IEEE VLSI, pp. 9–12, 2000
[62] M. Haenggi and D. Puccinelli. Routing in ad hoc networks: a case for long hops. IEEE Commun. Magazine, vol. 43, pp. 112–119, Oct. 2005
[63] R. Knopp and P.A. Humblet. Information capacity and power control in single-cell multiuser communications. Proc. IEEE ICC. , June 1995
[64] G. B. Giannakis, Y. Hua, P. Stoica et al.. Signal processing advances in wireless and mobile communications: trends in single- and multi-user systems, Prentice Hall PTR, 2001
[65] C. Comaniciu, N.B. Mandayam, and H.V. Poor. Wireless networks: multiuser detection in cross-layer design. Springer, 2005
[66] W. L. Huang and K. B. Letaief. Cross-layer scheduling and power control combined with adaptive modulation for wireless ad-hoc networks. IEEE Trans. Comm , Vol. 55 , Issue 4, pp. 728– 739 , April 2007
[67] J. Lee , R.V. Sonalkar and J.M. Cioffi. Multiuser bit loading for multicarrier systems. IEEETrans. Comm., Vol. 54, Issue 7, pp. 1170– 1174, July 2006
[68] L. Georgiadis, M.J. Neely and L. Tassiulas. Resource Allocation and Cross Layer Control in Wireless Networks. Now Publishers Inc., 2006
[69] I. Mitola, J. Maguire. Cognitive radio: making software radios more personal. IEEE Personal Communications 1999, vol.6 no.4, pp 13-18
[70] D. Cabric, S. Mishra, and R. W. Brodersen. Implementation issues in spectrum sensing for cognitive radios. Proc. IEEE Asil. Conf. signals, Sys., and Comp., (ACSSC 2004)
[71] FCC. ET Docket No. 03-322. Notice of proposed rule making and order. December 2003
[72] I. F. Akyildiz, W.-Y Lee, M. C. Vuran, et al.. A survey on spectrum management in cognitive radio networks. IEEE Commun. Mag., pp. 40–48, April 2008
[73] 3GPP TS 36.300 V9.0.0. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (E-UTRAN); overall description; Release 9. June 2009
[74] X. Zhou, G. Y. Li, and Y. H. Kwon, et al.. Detection timing and channel selection for periodic spectrum sensing in cognitive radio. Proc. IEEE Global Telecommun Conf., Dec. 2008
[75] A. Hoang and Y.-C. Liang. Adaptive scheduling of spectrum sensing periods in cognitive radio networks. Proc. IEEE Global Telecommun. Conf., Nov. 2007, pp. 3128–3132
[76] Y. Pei, A. Hoang, and Y-C. Liang. Sensing-throughput tradeoff in cognitive radio networks: how frequently should spectrum sensing be carried out?. Proc. Personal, Indoor and Mobile Radio Commun., Sept. 2007, pp. 1–5
[77] P. Wang, M. Zhao, and L. Xiao, et al.. Power allocation in OFDM-based cognitive radio systems. Proc. IEEE Global Telecommun. Conf., Nov. 2007, pp. 4061–4065
[78] G. Miao, N. Himayat, and G. Y. Li. Energy-efficient transmission in frequency-selective channels. Proc. IEEE Global Telecommun. Conf., Dec. 2008
[79] G. Ganesan and G. Y. Li. Cooperative spectrum sensing in cognitive radio - part I: two user networks. IEEE Trans.Commun., vol. 6, no. 6, pp. 2204–2213, June 2007
[80] G. Ganesan and G. Y. Li. Cooperative spectrum sensing in cognitive radio - part II: multiuser networks. IEEE Trans. Commun., vol. 6, no.6, pp. 2214–2222, June 2007
[81] J. Jia, J. Zhang, and Q. Zhang. Cooperative relay for cognitive radio networks. in Proc. IEEE INFOCOM, Apr. 2009, pp. 2304–2312
[82] R. Kwan, C. Leung, and J. Zhang. Resource allocation in an LTE cellular communication system. Proc. IEEE Int. Conf. Commun., Dresden, German, pp. 1-5, June 2009
[83] A. Bletsas, A. Khisti, and D. P. Reed, et al.. A simple cooperative diversity method based on network path selection. IEEE Sel. Areas Commun., vol. 24, no. 3, pp. 659–672, Mar. 2006
[84] X. Zhou, J. Ma, and G. Y. Li, et al.. Probability-based optimization of inter-sensing duration and power control in cognitive radio. IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 4922–4927, Oct. 2009
[85] A. Bletsas, A. Khisti, and D. P. Reed, et al.. A simple cooperative diversity method based on network path selection. IEEE Sel. Areas Commun., vol. 24, no. 3, pp. 659–672, Mar. 2006
[86] K. J. R. Liu, A. K. Sadek, and W. Su, et al.. Cooperative communications and networking. Cambridge University Press, 2009
[87] J. Mietzner, L. Lampe, and R. Schober. Distributed transmit power allocation for multihop cognitive-radio systems. IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 5187–5201, Oct. 2009
[88] H. G. Myung, J. Lim, and David J. Goodman. Single carrier FDMA for uplink wireless transmission. IEEE Veh. Tech. Mag., vol.1, no.3, pp. 30–38, 2006
[89] R1-050507. Soft frequency reuse scheme for UTRAN LTE. Huawei. 3GPP TSG RAN WG1 Meeting. Athens, Greece, May 2005
[90] X. Mao, A. Maaref, and K. Teo. Adaptive soft frequency reuse for intercell interference coordination in SC-FDMA based 3GPP LTE uplink. Proc. of IEEE GLOBECOM 2008, Nov. 2008, pp. 1–6
[91] I. C. Wong, O. Oteri, and W. McCoy. Optimal resource allocation in uplink SC-FDMA systems. IEEE Trans. Wireless Commu., vol.8, no.5, pp. 2161–2165, May 2009
[92] X. Qiu and K. Chawla. On the performance of adaptive modulation in cellular systems. IEEE Trans. Commu., vol. 47, no.6, pp. 884–895, June. 1999
[93] 3GPP TS 36.213 V9.0.0. Evolved universal terrestrial radio access (EUTRA); physical layer procedures; Release 9. Dec. 2009
[94] R. Giuliano and F. Mazzenga. Exponential effective SINR approximations for OFDM/OFDMA based cellular system planning. IEEE Trans. Wireless Commu., vol.8, no.9, pp. 4434–4439, 2009
[95] S. Lee, I. Pefkianakis, and A. Meyerson, et al.. Proportional fair frequency-domain packet scheduling for 3GPP LTE uplink. Proc. of IEEE INFOCOM, Apr. 2009
[96] Y. Chen, S.-Q. Zhang, and S.-G. Xu, et al.. Fundamental tradeoffs on green wireless networks. To appear on IEEE Commun.Mag
[97] G. Y. Li, Z.-K. Xu, and C. Xiong, et al.. Energy-efficient wireless communications: tutorial, survey, and open issues. To appear on IEEE Wireless Commun. Mag
[98] G.-W. Miao, N. Himayat, and G. Y. Li, et al.. Distributed interference-aware energy-efficient power optimization. To appear on IEEE Trans. Wireless Commun
[99] J.-C. Fan, Q.-Y. Yin, and G. Y. Li, et al.. Adaptive block-level resource allocation in OFDMA networks. Submited to IEEE 2011 Int’l Conf. Comput. Commun. Networks, Maui, Hawaii, July-August, 2011
[100] L.-Y. Li, G. Wu, and H.-B. Xu, et al.. Joint Power Control and Resource Allocation for Interference Mitigation in LTE Uplink Systems. To appear in the 45th Conf. Inf. Sci. and Sys., Baltimore, MD, March 2011
[101] M. McHenry, E. Livsucs, T. Nguyen, et al.. XG dynamic spectrum access field test results. IEEE Commun. Mag., 2007, vol.45 no. 6, pp 51-517
[102] P. D. Stran. Game theory and strategy. Mathematical Association of America, 1993
[103] A. J. Goldsmith and P. P. Varaiya. Capacity of fading channels with channel side information. IEEE Trans. Inf. Theory., vol. 43, pp. 1986–1992, July 1997
[104] J. Jang and K. B. Lee. Transmit power adaptation for multiuser OFDM systems. IEEE J. Sel. Areas Commun., vol. 21, pp. 171–178, Feb. 2003
[105] R. J. McEliece and W. E. Stark. Channels with block interference. IEEE Trans. Inf. Theory., vol. 30, pp. 44–53, Jan. 1984
[106] A. Goldsmith. Wireless Communications. Cambridge University Press, 2005
[107] M. Hellebrandt, R. Mathar, and M. Scheibenbogen. Estimating position and velocity of mobiles in a cellular radio network. IEEE Trans. Veh. Tech., vol. 46
[108] G. Sun, J. Chen, W. Guo, et al.. Signal processing techniques in network aided positioning: a survey of state-of-the-art positioning designs. IEEE Sig. Processing Mag., vol. 22
[109] M. Pischella and J.-C. Belfiore. Power control in distributed cooperative OFDMA cellular networks. vol. 7, pp. 1900–1906, May 2008
[110] A. Kumar, D. Manjunath, and J. Kuri. Wireless Networking. Morgan Kaufmann, 2008
[111] D. Tse and P Viswanath. Fundamentals of wireless communication. Cambridge University Press, 2005
[112] C. E. Shannon. Communication in the presence of noise. Proc. IRE, vol. 37, pp. 10–21, Jan. 1949
[113] N. Feng, S. C. Mau, and N. B. Mandayam. Pricing and power control for joint network-centric and user-centric radio resource management. IEEE Trans. Commun., vol. 52, pp. 1547–1557, Sept. 2004
[114] B. Prabhakar, E. U. Biyikoglu, and A. E. Gamal. Energy-efficient transmission over a wireless link via lazy packet scheduling. Proc. IEEE Infocom 2001, vol. 1, pp. 386–394, Apr. 2001
[115] S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004
[116] K. C. Kiwiel and K. Murty. Convergence of the steepest descent method for minimizing quasiconvex functions. J. of Optimization Theory and Applications, vol. 89, pp. 221–226, Sept. 2005
[117] G. Miao, N. Himayat, and Y. Li. Energy-efficient transmission in frequency selective channels. Proc. IEEE Globecom 2008, pp. 1–5, Dec. 2008
[118] D. Fudenberg and J. Tirole. Game Theory. Cambridge, MA: MIT Press, 1991
[119] R. D. Yates. A framework for uplink power control in cellular radio systems. pp. 1341–1347, Sept. 1995
[120] S. M. Ross. Stochastic Process. John Wiley & Sons, Inc., 1996
[121] K. Feher. Advanced Digital Communications. Englewood Cliffis, NJ: Prentice-Hall, 1987
[122] Y. (G.) Li and G. L. St¨uber. OFDM for Wireless Communications. Springer, 2006
[123] H. Dai, A. F. Molisch, and H. V. Poor. Downlink capacity of interference-limited MIMO systems with joint detection. IEEE Trans. Wireless Commun., vol. 3, pp. 442–453, Mar. 2004
[124] S. Shamai and B. M. Zaidel. Enhancing the cellular downlink capacity via coprocessing at the transmitting end. Proc. Conf. Veh. Tech. Spring, 2005, vol. 3, pp. 1745–1749, 2001
[125] 3GPP TS 36.300 V9.0.0. Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (EUTRAN); overall description; Release 9. June 2009
[126] K. B. Letaief and Y. J. Zhang. Dynamic multiuser resource allocation and adaptation for wireless systems. IEEE Wireless Comm., Special issue on Smart Antennas, Vol. 13, Issue 4, Aug. 2006