蜂窝无线通信系统中的干扰抑制预均衡与协作空时预编码
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摘要
移动通信的快速发展要求加大网络覆盖,提高传输速率,同时要求容纳更多的用户。用户密度的提高导致小区内、中继站间、小区间和网络间的干扰日趋复杂,而不同的通信场景、移动速度、网络结构和用户行为模式也使得干扰形态多种多样,从而严重制约着通信网络容量与系统性能的进一步提升。在蜂窝无线通信系统设计中,如何有效抑制符号间干扰、共信道干扰、小区边缘的邻区干扰等复杂多变的干扰,迄今仍然是瓶颈,亟待研究解决。为此,本论文致力于从信道均衡和预编码角度探讨几种主要干扰的有效抑制问题,重点研究蜂窝无线网络的干扰抑制预均衡与协作空时预编码技术。
论文首先对由信道时延扩展引发的符号间干扰展开研究,提出了一种基于有限域变换的预均衡方案。信号在发送端经过基域Harley变换与有限域均衡后进入无线信道传输,由于基域Harley变换具有与离散傅里叶变换相同的卷积特性,所提方案与正交频分复用(OFDM)方案一样能有效地抑制符号间干扰。同时,较之OFDM,本方案有更优的峰平比性能,且对载波频率偏差不敏感。通过对发送数据实行插零处理,所提方案具备一定的纠错能力。理论分析与仿真结果表明,所提方案能获得多径分集增益,其误码率性能与峰平比性能均优于编码的OFDM传输,且对载波频率偏差不敏感。
其次,针对同一个小区内多个中继站复用传输引发的共道干扰,本文提出了一种适用于放大转发多中继蜂窝网的协作预编码方案。小区内的用户首先被划分为基站服务用户与中继服务用户。在两跳的传输过程中,基站通过集中式的TH预编码方式将用户数据发送给中继与基站服务用户；然后,中继间通过信道信息共享对接收到的信号进行干扰对齐的线性预编码处理,并将编码后的数据放大与发送至相应的中继服务用户；在第二跳中,基站采用干扰对齐方式服务一个新的基站服务用户。所提方案在实现无干扰传输的同时,能够最大程度的利用系统空间自由度,实现复用增益。论文分别针对基站服务用户与中继服务用户不同的预编码方式,对其遍历信道容量进行了理论分析,给出了各自的容量上限。仿真结果验证了所提方案在不同网络场景中的有效性,并表明与现有的算法相比,所提方案能够提供更高的系统吞吐率,且不受发送端定时误差的影响。
接着,通过研究下行多小区协作传输,本文提出了一种基站间协作传输的预编码方案。该方案能够同时抑制小区内与小区间共道干扰,其主要思想是结合干扰对齐与干扰预删除两种方式,分别对小区间与小区内共道干扰进行抑制。小区间使用干扰对齐能增加系统的空间复用度,而小区内干扰删除则为获取系统分集度提供了可能。为了使所提方案在实际系统中能有效应用,论文提出了一种基于传统迭代干扰对齐实现的预编码优化方案。理论分析与仿真结果表明,由于采用了预删除与预编码优化,所提方案较之传统干扰对齐方式能够提供更多的分集增益,具有更优的接收性能。
随后,通过研究多小区协作非相干传输,提出了一种多基站联合传输的酉空时调制方案。由于该方案在发送端与接收端均无需完备信道信息,因此适合在高移动性场景下的使用。在所提方案中,每个协作基站分别从共用的信号集中选取酉信号发送至共同的小区边缘用户,用户在接收到数据后利用最大似然检测技术恢复出每个协作基站发送的信号。相比于传统酉调制方式,基站之间的协作不仅有效的抑制了小区间干扰,还能提高该用户的传输效率。通过理论分析,论文给出了所提方案的成对错误概率闭合解,并基于该闭合解,提出了相应的信号集优化方案,以获取传输效率与可靠性之间的折衷。仿真结果表明,所提方案在块静止信道与时变信道下均适用。
最后,本论文研究了时间-频率双选信道下的协作预编码传输,提出了一种两小区协作预编码方案,能够同时抑制符号间干扰与多小区共道干扰。所提方案选取短帧传输,来克服信道的时间选择性,并利用时域预编码,将小区间的共道干扰与符号间干扰对齐至同一空间,并在接收端一并舍弃。由于无需插入循环前缀,所提方案节约了系统频谱与发射功率。此外,针对于信道估计与反馈时延导致的信道信息过期问题,提出了一种改进的最大似然方案。在设计中,作者同时考虑信道的时间相关性与反馈时延的影响,以提高检测精度。针对快时变信道下的多小区信道估计,提出了嵌入式导频的方案,并对信道估计均方差与基于最小均方差的导频序列设计进行了理论分析。仿真结果给出了所提方案的信道估计均方差与误码率性能,验证了所提方案在双选信道下的有效性。
With the rapid development of wireless communications, the demand for cellular network keeps increasing with respect to higher data rate, larger cell coverage and higher supported user density. Higher user density leads to more severe interference, which prevents the data rate and system throughput from further increasing and becomes the major bottleneck of cellular communications. The diverse interference in wireless network could be very intricate, due to the various communication scenarios, user mobility, network topologies and user behaviors. Hence, how to eliminate the interference efficiently is not only a key factor to improve the system performance but also a challenging problem which requires much attention. This thesis aims at interference suppression issues from the aspects of channel equalization and precoding. To be more specific, serveral interference suppression schemes are proposed based on the pre-equalization and cooperative precoding to address mainly the co-channel interference (CCI) and inter-symbol interference problems.
The first part of the thesis discusses the elimination scheme of inter-symbol interference (ISI) which are caused by the channel delay spread. A pre-equalized transmission scheme based on a finite field transform is proposed to overcome the well known problems of orthogonal frequency-division multiplexing (OFDM) transmission, including large peak-to-average power ratio (PAPR) and sensitivity to carrier frequency offset (CFO). In the proposed scheme, the signals are processed with the finite field transform called basefield Hartley transform (BHT), which has the similar convolution property as discrete Fourier transform (DFT) for the ISI mitigation by applying a finite field pre-equalizer and quantization pre-equalizer at the transmitter. Padding zeros into the source data enables the error correction capability of proposed scheme with various coding rate. At the receiver, only a decoding scheme is required to recover the source data without any FFT operations, which leads to a simple receiver with low processing complexity. Simulation results show the proposed scheme outperforms coded OFDM in terms of bit-error rate and PAPR performance.
Then, a downlink multi-user transmission scheme is proposed for the amplify-and-forward (AF)-based multi-relay cellular network to support the multi-relay multiplexing and suppress the intra-cell co-channel interference. During the two phases of transmission, TH (Tomlinson-Harashima) precoding is firstly performed at basestation(BS) to support the data streams transmitted to both mobile-stations (MS) and relay-stations (RS), and then interference alignment (IA) is performed at both BS and RSs to achieve the interference-free communication in the second phase. Theoretical analysis is provided with respect to the throughput of different types of users, resulting the upper-bounds of ergodic channel capacity. The analysis and simulation results show that the joint applications of TH precoding and IA outperform other schemes in the presented multi-relay cellular network.
Thirdly, the thesis focuses on the design of downlink transmission protocols in multi-cell multi-user mobile networks, where co-channel interference has been recognized as a challenging issue particularly for the users close to the boundary of cells. The key idea of designed scheme is to jointly apply interference alignment and pre-cancelation to the addressed scenario, where the former technique can effectively increase the overall system throughput and the latter can significantly boost the diversity gains and reception reliability. To ensure that the proposed interference alignment protocols implemented efficiently in practice, a precoder optimization scheme is developed based on the well-known iterative interference leakage minimization scheme. Both analytic and simulation results have been developed to show the capacity and diversity gains obtained by using the proposed scheme.
Next, this thesis proposes a multi-cell cooperative transmission scheme based on unitary space-time modulation for the high mobility scenario, in which the channel state information (CSI) are not required at both transmitters and receivers. In the proposed scheme, each cooperative BS transmits an individual unitary signal from the common constellation set to the mobile unit which is located at the cell edge and suffers from severe inter-cell interference. Compared with traditional unitary space-time modulation, cooperation among nalti-cells not only eliminates the CCI but also increases the transmission rate by expanding the constellation size. Performance of error probability is analyzed for the proposed scenario with maximum-likelihood decoding, in which the exact pairwise error probability (PEP) is derived. Additionally, constellation optimization for cooperative transmission is also discussed to achieve a balance between transmission efficiency and reliability. Simulation results are provided to confirm the effectiveness of the proposed scheme in both block-fading channels and fast-fading channels.
The last part of the thesis still studies the multi-cell cooperation under the high mobility scenario, in which the channels are assumed to be both time and frequency selective. A novel precoding scheme is proposed to eliminate both ISI and CCI based on the two-cell transmission. In the proposed scheme, short size blocks are applied to alleviate the time variation before both ISI and CCI are aligned to same dimension for suppression. The avoidance of cyclic prefix (CP) saves spectrum and power for the system. Additionally, since the feedback CSI could be outdated due to the time-variation of channels and estimation delay, an enhanced maximum-likelihood(ML) receiver is derived based on original ML receiver, in which the channel time correlation and feedback delay are taken into consideration. Furthermore, to make the proposed scheme applicable in practical scenario, a structure of embedded pilot is proposed and the mean square error (MSE) of channel estimation is analyzed by using the least-square (LS) method. Simulation results confirm the validity of the proposed scheme in doubly selective channels with both perfect CSI and estimated CSI.
论文首先对由信道时延扩展引发的符号间干扰展开研究,提出了一种基于有限域变换的预均衡方案。信号在发送端经过基域Harley变换与有限域均衡后进入无线信道传输,由于基域Harley变换具有与离散傅里叶变换相同的卷积特性,所提方案与正交频分复用(OFDM)方案一样能有效地抑制符号间干扰。同时,较之OFDM,本方案有更优的峰平比性能,且对载波频率偏差不敏感。通过对发送数据实行插零处理,所提方案具备一定的纠错能力。理论分析与仿真结果表明,所提方案能获得多径分集增益,其误码率性能与峰平比性能均优于编码的OFDM传输,且对载波频率偏差不敏感。
其次,针对同一个小区内多个中继站复用传输引发的共道干扰,本文提出了一种适用于放大转发多中继蜂窝网的协作预编码方案。小区内的用户首先被划分为基站服务用户与中继服务用户。在两跳的传输过程中,基站通过集中式的TH预编码方式将用户数据发送给中继与基站服务用户；然后,中继间通过信道信息共享对接收到的信号进行干扰对齐的线性预编码处理,并将编码后的数据放大与发送至相应的中继服务用户；在第二跳中,基站采用干扰对齐方式服务一个新的基站服务用户。所提方案在实现无干扰传输的同时,能够最大程度的利用系统空间自由度,实现复用增益。论文分别针对基站服务用户与中继服务用户不同的预编码方式,对其遍历信道容量进行了理论分析,给出了各自的容量上限。仿真结果验证了所提方案在不同网络场景中的有效性,并表明与现有的算法相比,所提方案能够提供更高的系统吞吐率,且不受发送端定时误差的影响。
接着,通过研究下行多小区协作传输,本文提出了一种基站间协作传输的预编码方案。该方案能够同时抑制小区内与小区间共道干扰,其主要思想是结合干扰对齐与干扰预删除两种方式,分别对小区间与小区内共道干扰进行抑制。小区间使用干扰对齐能增加系统的空间复用度,而小区内干扰删除则为获取系统分集度提供了可能。为了使所提方案在实际系统中能有效应用,论文提出了一种基于传统迭代干扰对齐实现的预编码优化方案。理论分析与仿真结果表明,由于采用了预删除与预编码优化,所提方案较之传统干扰对齐方式能够提供更多的分集增益,具有更优的接收性能。
随后,通过研究多小区协作非相干传输,提出了一种多基站联合传输的酉空时调制方案。由于该方案在发送端与接收端均无需完备信道信息,因此适合在高移动性场景下的使用。在所提方案中,每个协作基站分别从共用的信号集中选取酉信号发送至共同的小区边缘用户,用户在接收到数据后利用最大似然检测技术恢复出每个协作基站发送的信号。相比于传统酉调制方式,基站之间的协作不仅有效的抑制了小区间干扰,还能提高该用户的传输效率。通过理论分析,论文给出了所提方案的成对错误概率闭合解,并基于该闭合解,提出了相应的信号集优化方案,以获取传输效率与可靠性之间的折衷。仿真结果表明,所提方案在块静止信道与时变信道下均适用。
最后,本论文研究了时间-频率双选信道下的协作预编码传输,提出了一种两小区协作预编码方案,能够同时抑制符号间干扰与多小区共道干扰。所提方案选取短帧传输,来克服信道的时间选择性,并利用时域预编码,将小区间的共道干扰与符号间干扰对齐至同一空间,并在接收端一并舍弃。由于无需插入循环前缀,所提方案节约了系统频谱与发射功率。此外,针对于信道估计与反馈时延导致的信道信息过期问题,提出了一种改进的最大似然方案。在设计中,作者同时考虑信道的时间相关性与反馈时延的影响,以提高检测精度。针对快时变信道下的多小区信道估计,提出了嵌入式导频的方案,并对信道估计均方差与基于最小均方差的导频序列设计进行了理论分析。仿真结果给出了所提方案的信道估计均方差与误码率性能,验证了所提方案在双选信道下的有效性。
With the rapid development of wireless communications, the demand for cellular network keeps increasing with respect to higher data rate, larger cell coverage and higher supported user density. Higher user density leads to more severe interference, which prevents the data rate and system throughput from further increasing and becomes the major bottleneck of cellular communications. The diverse interference in wireless network could be very intricate, due to the various communication scenarios, user mobility, network topologies and user behaviors. Hence, how to eliminate the interference efficiently is not only a key factor to improve the system performance but also a challenging problem which requires much attention. This thesis aims at interference suppression issues from the aspects of channel equalization and precoding. To be more specific, serveral interference suppression schemes are proposed based on the pre-equalization and cooperative precoding to address mainly the co-channel interference (CCI) and inter-symbol interference problems.
The first part of the thesis discusses the elimination scheme of inter-symbol interference (ISI) which are caused by the channel delay spread. A pre-equalized transmission scheme based on a finite field transform is proposed to overcome the well known problems of orthogonal frequency-division multiplexing (OFDM) transmission, including large peak-to-average power ratio (PAPR) and sensitivity to carrier frequency offset (CFO). In the proposed scheme, the signals are processed with the finite field transform called basefield Hartley transform (BHT), which has the similar convolution property as discrete Fourier transform (DFT) for the ISI mitigation by applying a finite field pre-equalizer and quantization pre-equalizer at the transmitter. Padding zeros into the source data enables the error correction capability of proposed scheme with various coding rate. At the receiver, only a decoding scheme is required to recover the source data without any FFT operations, which leads to a simple receiver with low processing complexity. Simulation results show the proposed scheme outperforms coded OFDM in terms of bit-error rate and PAPR performance.
Then, a downlink multi-user transmission scheme is proposed for the amplify-and-forward (AF)-based multi-relay cellular network to support the multi-relay multiplexing and suppress the intra-cell co-channel interference. During the two phases of transmission, TH (Tomlinson-Harashima) precoding is firstly performed at basestation(BS) to support the data streams transmitted to both mobile-stations (MS) and relay-stations (RS), and then interference alignment (IA) is performed at both BS and RSs to achieve the interference-free communication in the second phase. Theoretical analysis is provided with respect to the throughput of different types of users, resulting the upper-bounds of ergodic channel capacity. The analysis and simulation results show that the joint applications of TH precoding and IA outperform other schemes in the presented multi-relay cellular network.
Thirdly, the thesis focuses on the design of downlink transmission protocols in multi-cell multi-user mobile networks, where co-channel interference has been recognized as a challenging issue particularly for the users close to the boundary of cells. The key idea of designed scheme is to jointly apply interference alignment and pre-cancelation to the addressed scenario, where the former technique can effectively increase the overall system throughput and the latter can significantly boost the diversity gains and reception reliability. To ensure that the proposed interference alignment protocols implemented efficiently in practice, a precoder optimization scheme is developed based on the well-known iterative interference leakage minimization scheme. Both analytic and simulation results have been developed to show the capacity and diversity gains obtained by using the proposed scheme.
Next, this thesis proposes a multi-cell cooperative transmission scheme based on unitary space-time modulation for the high mobility scenario, in which the channel state information (CSI) are not required at both transmitters and receivers. In the proposed scheme, each cooperative BS transmits an individual unitary signal from the common constellation set to the mobile unit which is located at the cell edge and suffers from severe inter-cell interference. Compared with traditional unitary space-time modulation, cooperation among nalti-cells not only eliminates the CCI but also increases the transmission rate by expanding the constellation size. Performance of error probability is analyzed for the proposed scenario with maximum-likelihood decoding, in which the exact pairwise error probability (PEP) is derived. Additionally, constellation optimization for cooperative transmission is also discussed to achieve a balance between transmission efficiency and reliability. Simulation results are provided to confirm the effectiveness of the proposed scheme in both block-fading channels and fast-fading channels.
The last part of the thesis still studies the multi-cell cooperation under the high mobility scenario, in which the channels are assumed to be both time and frequency selective. A novel precoding scheme is proposed to eliminate both ISI and CCI based on the two-cell transmission. In the proposed scheme, short size blocks are applied to alleviate the time variation before both ISI and CCI are aligned to same dimension for suppression. The avoidance of cyclic prefix (CP) saves spectrum and power for the system. Additionally, since the feedback CSI could be outdated due to the time-variation of channels and estimation delay, an enhanced maximum-likelihood(ML) receiver is derived based on original ML receiver, in which the channel time correlation and feedback delay are taken into consideration. Furthermore, to make the proposed scheme applicable in practical scenario, a structure of embedded pilot is proposed and the mean square error (MSE) of channel estimation is analyzed by using the least-square (LS) method. Simulation results confirm the validity of the proposed scheme in doubly selective channels with both perfect CSI and estimated CSI.
引文
[1]刘秋妍.无线网络同信道干扰性能分析方法研究.北京交通大学博士学位论文.2012
[2]A. Agarwal, P. Kumar. Capacity bounds for ad hoc and hybrid wireless networks. ACM SIGCOMM Computer Communication Review.2004,34(3):71-81
[3]N. Benvenuto, L. Bettella, R. Marchesani. Performance of the Viterbi algorithm for interleaved convolutional codes. Vehicular Technology, IEEE Transactions on.1998, 47(3):919-923
[4]C. Wan, J. G. Andrews. Improved Performance Analysis for Maximal Ratio Combining in Asynchronous CDMA Channels. Wireless Communications, IEEE Transactions on. 2007,6(9):3297-3305
[5]Y. Liuqing, G. B. Giannakis. A general model and SINR analysis of low duty-cycle UWB access through multipath with narrowband interference and rake reception. Wireless Communications, IEEE Transactions on.2005,4(4):1818-1833
[6]L. Seongjoo, H. Sangyun, K. Jaeseok. Low-complexity architecture of rake receiver for multi-code CDMA system. Electronics Letters.1998,34(14):1382-1383
[7]L. Cimini, Jr. Analysis and Simulation of a Digital Mobile Channel Using Orthogonal Frequency Division Multiplexing. Communications, IEEE Transactions on.1985, 33(7):665-675
[8]D. Astely, E. Dahlman, A. Furuskar, et al. LTE:the evolution of mobile broadband. Communications Magazine, IEEE.2009,47(4):44-51
[9]S. Srikanth, P. A. Murugesa Pandian, X. Fernando. Orthogonal frequency division multiple access in WiMAX and LTE:a comparison. Communications Magazine, IEEE. 2012,50(9):153-161
[10]S. Parkvall, A. Furuska, E. Dahlman, et al. Evolution of LTE toward IMT-advanced. Communications Magazine, IEEE.2011,49(2):84-91
[11]J. G. Andrews, R. Chen. Broadband wireless access with WiMax/802.16:Current performance benchmarks and future potential. IEEE communications magazine.2005: 130
[12]L. Nuaymi, WiMAX:technology for broadband wireless access:Wiley,2007
[13]S. K. Deng, M. C. Lin. OFDM PAPR reduction using clipping with distortion control. Communications,2005. ICC 2005.2005 IEEE International Conference on,2005: 2563-2567
[14]B. K. Khoo, S. Y. Le Goff, C. C. Tsimenidis, et al. OFDM PAPR reduction using selected mapping without side information. Communications,2007. ICC'07. IEEE International Conference on,2007:4341-4345
[15]S. H. Han, J. H. Lee. PAPR reduction of OFDM signals using a reduced complexity PTS technique. Signal Processing Letters, IEEE.2004,11(11):887-890
[16]S. H. Han, J. H. Lee. An overview of peak-to-average power ratio reduction techniques for multicarrier transmission. Wireless Communications, IEEE.2005,12(2):56-65
[17]M. Ghogho, A. Swami, G. B. Giannakis. Optimized null-subcarrier selection for CFO estimation in OFDM over frequency-selective fading channels. Global Telecommunications Conference,2001. GLOBECOM'01. IEEE,2001:202-206
[18]X. Ma, C. Tepedelenlioglu, G. B. Giannakis, et al. Non-data-aided carrier offset estimators for OFDM with null subcarriers:identifiability, algorithms, and performance. Selected Areas in Communications, IEEE Journal on.2001,19(12): 2504-2515
[19]K. Sathananthan, C. Tellambura. Probability of error calculation of OFDM systems with frequency offset. Communications, IEEE Transactions on.2001,49(11): 1884-1888
[20]B. Chen, H. Wang. Blind estimation of OFDM carrier frequency offset via oversampling. Signal Processing, IEEE Transactions on.2004,52(7):2047-2057
[21]D. Falconer, S. L. Ariyavisitakul, A. Benyamin-Seeyar, et al. Frequency domain equalization for single-carrier broadband wireless systems. Communications Magazine, IEEE.2002,40(4):58-66
[22]A. Gusmao, R. Dinis, N. Esteves. On frequency-domain equalization and diversity combining for broadband wireless communications. Communications, IEEE Transactions on.2003,51(7):1029-1033
[23]Y. Wang, X. Dong. Comparison of frequency offset and timing offset effects on the performance of SC-FDE and OFDM over UWB channels. Vehicular Technology, IEEE Transactions on.2009,58(1):242-250
[24]H. G. Myung. Technical overview of 3GPP LTE. Polytechnic University of New York. 2008
[25]Q. Li, G. Li, W. Lee, et al. MIMO techniques in WiMAX and LTE:a feature overview. Communications Magazine, IEEE.2010,48(5):86-92
[26]G. Charalabopoulos, P. Stavroulakis, A. H. Aghvami. Pre-post-and balanced equalization in OFDM. Vehicular Technology Conference,2003. VTC 2003-Fall.2003 IEEE 58th,2003:3145-3148
[27]R. L. U. Choi, R. D. Murch. Frequency domain pre-equalization with transmit diversity for MISO broadband wireless communications. Vehicular Technology Conference,2002. Proceedings. VTC 2002-Fall.2002 IEEE 56th,2002:1787-1791
[28]D. Huaiyu, A. F. Molisch, H. V. Poor. Downlink capacity of interference-limited MIMO systems with joint detection. Wireless Communications, IEEE Transactions on. 2004,3(2):442-453
[29]A. Burg, M. Borgmann, C. Simon, et al. Performance tradeoffs in the VLSI implementation of the sphere decoding algorithm.3G Mobile Communication Technologies,2004.3G 2004. Fifth IEE International Conference on,2004:93-97
[30]C. Wan, J. G. Andrews. The Capacity Gain from Base Station Cooperative Scheduling in a MIMO DPC Cellular System. Information Theory,2006 IEEE International Symposium on,2006:1224-1228
[31]A. Tolli, H. Pennanen, P. Komulainen. On the Value of Coherent and Coordinated Multi-Cell Transmission. Communications Workshops,2009. ICC Workshops 2009. IEEE International Conference on,2009:1-5
[32]S. A. Jafar, A. J. Goldsmith. Transmitter optimization for multiple antenna cellular systems. Information Theory,2002. Proceedings.2002 IEEE International Symposium on,2002:50
[33]A. A. M. Saleh, A. Rustako, R. Roman. Distributed Antennas for Indoor Radio Communications. Communications, IEEE Transactions on.1987,35(12):1245-1251
[34]C. Wan, J. G. Andrews. Downlink performance and capacity of distributed antenna systems in a multicell environment. Wireless Communications, IEEE Transactions on. 2007,6(1):69-73
[35]P. Marsch, G. Fettweis. A Framework for Optimizing the Uplink Performance of Distributed Antenna Systems under a Constrained Backhaul. Communications,2007. ICC'07. IEEE International Conference on,2007:975-979
[36]S. Shamai, B. M. Zaidel. Enhancing the cellular downlink capacity via co-processing at the transmitting end. Vehicular Technology Conference,2001. VTC 2001 Spring. IEEE VTS 53rd,2001:1745-1749
[37]O. Somekh, O. Simeone, Y. Bar-Ness, et al. CTH11-2:Distributed Multi-Cell Zero-Forcing Beamforming in Cellular Downlink Channels. Global Telecommunications Conference,2006. GLOBECOM'06. IEEE,2006:1-6
[38]O. Somekh, B. M. Zaidel, S. Shamai. Sum Rate Characterization of Joint Multiple Cell-Site Processing. Information Theory, IEEE Transactions on.2007,53(12): 4473.4497
[39]A. Stefanov, E. Erkip. Cooperative coding for wireless networks. Communications, IEEE Transactions on.2004,52(9):1470-1476
[40]T. Cover, A. E. L. Gamal. Capacity theorems for the relay channel. Information Theory, IEEE Transactions on.1979,25(5):572-584
[41]A. Sendonaris, E. Erkip, B. Aazhang. User cooperation diversity. Part Ⅰ. System description. Communications, IEEE Transactions on.2003,51(11):1927-1938
[42]A. Sendonaris, E. Erkip, B. Aazhang. User cooperation diversity. Part Ⅱ. Implementation aspects and performance analysis. Communications, IEEE Transactions on.2003,51(11):1939-1948
[43]M. Janani, A. Hedayat, T. E. Hunter, et al. Coded cooperation in wireless communications:space-time transmission and iterative decoding. Signal Processing, IEEE Transactions on.2004,52(2):362-371
[44]Q. Zhao, H. Li. Performance of differential modulation with wireless relays in Rayleigh fading channels. Communications Letters, IEEE.2005,9(4):343-345
[45]T. Himsoon, W. Su, K. J. R. Liu. Differential transmission for amplify-and-forward cooperative communications. Signal Processing Letters, IEEE.2005,12(9):597-600
[46]D. Chen, J. N. Laneman. Cooperative diversity for wireless fading channels without channel state information. Signals, Systems and Computers,2004. Conference Record of the Thirty-Eighth Asilomar Conference on,2004:1307-1312
[47]A. Wittneben, I. Hammerstrom. Multiuser zero forcing relaying with noisy channel state information [wireless ad hoc network applications]. Wireless Communications and Networking Conference,2005 IEEE,2005:1018-1023
[48]Z. Jian, M. Kuhn, A. Wittneben, et al. Cooperative Transmission Schemes for Decode-and-Forward Relaying. Personal, Indoor and Mobile Radio Communications, 2007. PIMRC 2007. IEEE 18th International Symposium on,2007:1-5
[49]N. Devroye, N. B. Mehta, A. F. Molisch. Asymmetric Cooperation Among Relays with Linear Precoding. Global Telecommunications Conference,2007. GLOBECOM'07. IEEE,2007:4391-4396
[50]G. Atia, A. F. Molisch. Cooperative Relaying with Imperfect Channel State Information. Global Telecommunications Conference,2008. IEEE GLOBECOM 2008. IEEE,2008: 1-6
[51]L. Hang, W. Fangxiang, K. Jinghua, et al. Multi-User Precoding and Energy-Efficient Relaying Scheme in Multi-Relay Systems. Communications Workshops (ICC),2011 IEEE International Conference on,2011:1-5
[52]A. Sanderovich, O. Somekh, S. Shamai. Uplink Macro Diversity with Limited Backhaul Capacity. Information Theory,2007. ISIT 2007. IEEE International Symposium on,2007:11-15
[53]L. Falconetti, C. Hoymann, R. Gupta. Distributed Uplink Macro Diversity for Cooperating Base Stations. Communications Workshops,2009. ICC Workshops 2009. IEEE International Conference on,2009:1-5
[54]H. Zhang, H. Dai, Q. Zhou. Base station cooperation for multiuser MIMO:Joint transmission and BS selection. Conference on information sciences and systems,2004
[55]H. Zhang, H. Dai. Cochannel interference mitigation and cooperative processing in downlink multicell multiuser MIMO networks. EURASIP Journal on Wireless Communications and Networking.2004,2004(2):222-235
[56]H. Weingarten, Y. Steinberg, S. Shamai. The capacity region of the Gaussian multiple-input multiple-output broadcast channel. Information Theory, IEEE Transactions on.2006,52(9):3936-3964
[57]T. Yoo, A. Goldsmith. Optimality of zero-forcing beamforming with multiuser diversity. Communications,2005. ICC 2005.2005 IEEE International Conference on,2005: 542-546
[58]U. Erez, S. Shamai, R. Zamir. Capacity and lattice strategies for canceling known interference. Information Theory, IEEE Transactions on.2005,51(11):3820-3833
[59]M. Vemula, D. Avidor, J. Ling, et al. Inter-cell coordination, opportunistic beamforming and scheduling. Communications,2006. ICC'06. IEEE International Conference on,2006:5319-5324
[60]B. Song, R. L. Cruz, B. D. Rao. Network duality for multiuser MIMO beamforming networks and applications. Communications, IEEE Transactions on.2007,55(3): 618-630
[61]L. Venturino, N. Prasad, X. Wang. Coordinated linear beamforming in downlink multi-cell wireless networks. Wireless Communications, IEEE Transactions on.2010, 9(4):1451-1461
[62]V. R. Cadambe, S. A. Jafar. Interference Alignment and Degrees of Freedom of the K-User Interference Channel. Information Theory, IEEE Transactions on.2008,54(8): 3425-3441
[63]K. Gomadam, V. R. Cadambe, S. A. Jafar. Approaching the capacity of wireless networks through distributed interference alignment. Global Telecommunications Conference,2008. IEEE GLOBECOM 2008. IEEE,2008:1-6
[64]R. Tresch, M. Guillaud. Cellular interference alignment with imperfect channel knowledge. Communications Workshops,2009. ICC Workshops 2009. IEEE International Conference on,2009:1-5
[65]B. M. Hochwald, T. L. Marzetta. Unitary space-time modulation for multiple-antenna communications in Rayleigh flat fading. Information Theory, IEEE Transactions on. 2000,46(2):543-564
[66]B. L. Hughes. Differential space-time modulation. Information Theory, IEEE Transactions on.2000,46(7):2567-2578
[67]B. M. Hochwald, W. Sweldens. Differential unitary space-time modulation. Communications, IEEE Transactions on.2000,48(12):2041-2052
[68]C. Shan, A. Nallanathan, P. Y. Kam. A new class of signal constellations for differential unitary space-time modulation (DUSTM). Communications Letters, IEEE.2004,8(1): 1-3
[69]M. Hajiaghayi, C. Tellambura. Unitary signal constellations for differential space-time modulation. Communications Letters, IEEE.2007,11(1):25-27
[70]J. Wang, M. K. Simon, K. Yao. On the optimum design of differential unitary space-time modulation. Global Telecommunications Conference,2003. GLOBECOM'03. IEEE,2003:1968-1972
[71]Q. Zhao, H. Li. Differential modulation for cooperative wireless systems. Signal Processing, IEEE Transactions on.2007,55(5):2273-2283
[72]T. Wang, Y. Yao, G. B. Giannakis. Non-coherent distributed space-time processing for multiuser cooperative transmissions. Wireless Communications, IEEE Transactions on. 2006,5(12):3339-3343
[73]G. B. Giannakis, C. Tepedelenlioglu. Basis expansion models and diversity techniques for blind identification and equalization of time-varying channels. Proceedings of the IEEE.1998,86(10):1969-1986
[74]G. B. Giannakis, X. Ma, G. Leus, et al. Space-time-Doppler coding over time-selective fading channels with maximum diversity and coding gains. Acoustics, Speech, and Signal Processing (ICASSP),2002 IEEE International Conference on,2002: III-2217-III-2220
[75]X. Ma, G. B. Giannakis. Maximum-diversity transmissions over doubly selective wireless channels. Information Theory, IEEE Transactions on.2003,49(7):1832-1840
[76]X. Ma, G. B. Giannakis, S. Ohno. Optimal training for block transmissions over doubly selective wireless fading channels. Signal Processing, IEEE Transactions on.2003, 51(5):1351-1366
[77]X. Ma, G. B. Giannakis. Space-time-multipath coding using digital phase sweeping or circular delay diversity. Signal Processing, IEEE Transactions on.2005,53(3): 1121-1131
[78]L. Rugini, P. Banelli. BER of OFDM systems impaired by carrier frequency offset in multipath fading channels. Wireless Communications, IEEE Transactions on.2005, 4(5):2279-2288
[79]J. P. C. L. Miranda, H. M. d. Oliveira. On Galois-division multiple access systems: figures of merit and performance evaluation. XIX Simposio Brasileiro de Telecommunication, Fortaleza CE.2001
[80]H. M. d. Oliveira, J. P. C. L. Miranda, R. M. C. d. Souza. Spread spectrum based on finite field Fourier transforms. ICSECIT 2001 International Conference on Systems Engineering, Communications and Information Technologies, Punta Arenas, Chile. Apr. 2001
[81]F. Fekri, D. B. Williams. Multicarrier modulation via finite-field transforms. Digital Signal Processing Workshop,2002 and the 2nd Signal Processing Education Workshop. Proceedings of 2002 IEEE 10th,2002:16-19
[82]R. M. C. De Souza, H. De Oliveira, A. Kauffman, et al. The Hartley transform in a finite field. Revista da Sociedade Brasileira de Telecomunicacoes.1999,14(1):46-54
[83]R. N. Bracewell. Discrete hartley transform. JOSA.1983,73(12):1832-1835
[84]J. Hong, M. Vetterli. Hartley transforms over finite fields. Information Theory, IEEE Transactions on.1993,39(5):1628-1638
[85]J. Hong, M. Vetterli, P. Duhamel. Basefield transforms with the convolution property. Proceedings of the IEEE.1994,82(3):400-412
[86]J. Miranda, H. De Oliveira. On Galois-Division Multiple Access Systems:Figures of Merit and Performance Evaluation. Anais do 19o Simposio Brasileiro de Telecomunicacoes, Fortaleza CE.2001
[87]C. Windpassinger, Detection and precoding for multiple input multiple output channels: Shaker,2004
[88]D. Divsalar, M. K. Simon. The design of trellis coded MPSK for fading channels: Performance criteria. Communications, IEEE Transactions on.1988,36(9):1004-1012
[89]V. Tarokh, N. Seshadri, A. R. Calderbank. Space-time codes for high data rate wireless communication:Performance criterion and code construction. Information Theory, IEEE Transactions on.1998,44(2):744-765
[90]G. H. Golub, C. F. Van Loan, Matrix computations vol.3:Johns Hopkins University Press,1996
[91]C. Tepedelenlioglu. Maximum multipath diversity with linear equalization in precoded OFDM systems. Information Theory, IEEE Transactions on.2004,50(1):232-235
[92]T. Pollet, M. Van Bladel, M. Moeneclaey. BER sensitivity of OFDM systems to carrier frequency offset and Wiener phase noise. Communications, IEEE Transactions on. 1995,43(234):191-193
[93]J. N. Laneman, D. N. C. Tse, G. W. Wornell. Cooperative diversity in wireless networks:Efficient protocols and outage behavior. Information Theory, IEEE Transactions on.2004,50(12):3062-3080
[94]S. Gollakota, S. D. Perli, D. Katabi. Interference alignment and cancellation. ACM SIGCOMM Computer Communication Review,2009:159-170
[95]B. Ozdemir, O. Gurbuz. Scheduling approach for MIMO with Tomlinson-Harashima precoding. Vehicular Technology Conference,2006. VTC 2006-Spring. IEEE 63rd, 2006:329-333
[96]R. A. Horn, C. R. Johnson, Matrix analysis:Cambridge university press,1990
[97]H. Long, F. Wang, J. Kuang, et al. Multi-User Precoding and Energy-Efficient Relaying Scheme in Multi-Relay Systems. Communications Workshops (ICC),2011 IEEE International Conference on,2011:1-5
[98]H. Meghdadi, J. P. Cances. Performance analysis of a cooperative multiple access relaying scheme. Proceedings of the 6th International Wireless Communications and Mobile Computing Conference,2010:1065-1069
[99]T. D. Nguyen, O. Berder, O. Sentieys. Impact of transmission synchronization error and cooperative reception techniques on the performance of cooperative MIMO systems. Communications,2008. ICC'08. IEEE International Conference on,2008: 4601-4605
[100]C. Suh, D. Tse. Interference alignment for cellular networks. Communication, Control, and Computing,2008 46th Annual Allerton Conference on,2008:1037-1044
[101]W. Shin, N. Lee, J. B. Lim, et al. On the design of interference alignment scheme for two-cell MIMO interfering broadcast channels. Wireless Communications, IEEE Transactions on.2011,10(2):437-442
[102]B. Zhuang, R. A. Berry, M. L. Honig. Interference alignment in MIMO cellular networks. Acoustics, Speech and Signal Processing (ICASSP),2011 IEEE International Conference on,2011:3356-3359
[103]A. Mathal, P. Moschopoulos. A form of multivariate gamma distribution. Annals of the Institute of Statistical Mathematics.1992,44(1):97-106
[104]D. Liu, Q. Zhang, Q. Chen. Structures and performance of noncoherent receivers for unitary space-time modulation on correlated fast-fading channels. Vehicular Technology, IEEE Transactions on.2004,53(4):1116-1125
[105]B. M. Hochwald, T. L. Marzetta, T. J. Richardson, et al. Systematic design of unitary space-time constellations. Information Theory, IEEE Transactions on.2000,46(6): 1962-1973
[106]W. Jakes, Mobile radio propagation:Wiley-IEEE Press,2009
[107]J. Ziyan, S. Handa, F. Sasamori, et al. Multiple-symbol differential detection for unitary space-time-frequency coding. IEICE transactions on communications.2010, 93(1):90-98
[108]E. U. T. R. Access. Physical Channels and Modulation.3GPP TS.2009,36:V8
[109]M. Qingyu, W. Wenbo, Y. Dacheng, et al. An Investigation of Inter-cell Interference in UTRA-TDD system. Vehicular Technology Conference,2000. IEEE VTS-Fall VTC 2000.52nd,2000:3002-3007
[110]L. Zheng, D. N. C. Tse. Diversity and multiplexing:A fundamental tradeoff in multiple-antenna channels. Information Theory, IEEE Transactions on.2003,49(5): 1073-1096
[111]X. Ma, G. B. Giannakis. Maximum-diversity transmissions over time-selective wireless channels. Wireless Communications and Networking Conference,2002. WCNC2002. 2002 IEEE,2002:497-501
[112]Q. Guo, L. Ping, D. Huang. A low-complexity iterative channel estimation and detection technique for doubly selective channels. Wireless Communications, IEEE Transactions on.2009,8(8):4340-4349
[113]J. J. Van de Beek, O. Edfors, M. Sandell, et al. On channel estimation in OFDM systems. Vehicular Technology Conference,1995 IEEE 45th,1995:815-819
[114]I. Barhumi, G. Leus, M. Moonen. Optimal training design for MIMO OFDM systems in mobile wireless channels. Signal Processing, IEEE Transactions on.2003,51(6): 1615-1624
[115]R. Xu, F. C. M. Lau. Performance analysis for MIMO systems using zero forcing detector over Rice fading channel. Circuits and Systems,2005. ISCAS 2005. IEEE International Symposium on,2005:4955-4958
[116]W. Tan, R. Gupta. On approximating the non-central Wishart distribution with Wishart distribution. Commun. Stat. Theory Method.1983,12(22):2589-2600
[117]D. Maiwald, D. Kraus. On moments of complex Wishart and complex inverse Wishart distributed matrices. Acoustics, Speech, and Signal Processing,1997. ICASSP-97., 1997 IEEE International Conference on,1997:3817-3820
[118]T. L. Tung, K. Yao, R. Hudson. Channel estimation and adaptive power allocation for performance and capacity improvement of multiple-antenna OFDM systems. Wireless Communications,2001.(SPAWC'01).2001 IEEE Third Workshop on Signal Processing Advances in,2001:82-85
[119]Universal mobile telecommunications system (UMTS); Spacial channel model for multiple input multiple output (MIMO) simulations (3GPP TR 25.996 version 8.0.0 Release 8),3GPP Std, ed:TR Patent 125996V8
[2]A. Agarwal, P. Kumar. Capacity bounds for ad hoc and hybrid wireless networks. ACM SIGCOMM Computer Communication Review.2004,34(3):71-81
[3]N. Benvenuto, L. Bettella, R. Marchesani. Performance of the Viterbi algorithm for interleaved convolutional codes. Vehicular Technology, IEEE Transactions on.1998, 47(3):919-923
[4]C. Wan, J. G. Andrews. Improved Performance Analysis for Maximal Ratio Combining in Asynchronous CDMA Channels. Wireless Communications, IEEE Transactions on. 2007,6(9):3297-3305
[5]Y. Liuqing, G. B. Giannakis. A general model and SINR analysis of low duty-cycle UWB access through multipath with narrowband interference and rake reception. Wireless Communications, IEEE Transactions on.2005,4(4):1818-1833
[6]L. Seongjoo, H. Sangyun, K. Jaeseok. Low-complexity architecture of rake receiver for multi-code CDMA system. Electronics Letters.1998,34(14):1382-1383
[7]L. Cimini, Jr. Analysis and Simulation of a Digital Mobile Channel Using Orthogonal Frequency Division Multiplexing. Communications, IEEE Transactions on.1985, 33(7):665-675
[8]D. Astely, E. Dahlman, A. Furuskar, et al. LTE:the evolution of mobile broadband. Communications Magazine, IEEE.2009,47(4):44-51
[9]S. Srikanth, P. A. Murugesa Pandian, X. Fernando. Orthogonal frequency division multiple access in WiMAX and LTE:a comparison. Communications Magazine, IEEE. 2012,50(9):153-161
[10]S. Parkvall, A. Furuska, E. Dahlman, et al. Evolution of LTE toward IMT-advanced. Communications Magazine, IEEE.2011,49(2):84-91
[11]J. G. Andrews, R. Chen. Broadband wireless access with WiMax/802.16:Current performance benchmarks and future potential. IEEE communications magazine.2005: 130
[12]L. Nuaymi, WiMAX:technology for broadband wireless access:Wiley,2007
[13]S. K. Deng, M. C. Lin. OFDM PAPR reduction using clipping with distortion control. Communications,2005. ICC 2005.2005 IEEE International Conference on,2005: 2563-2567
[14]B. K. Khoo, S. Y. Le Goff, C. C. Tsimenidis, et al. OFDM PAPR reduction using selected mapping without side information. Communications,2007. ICC'07. IEEE International Conference on,2007:4341-4345
[15]S. H. Han, J. H. Lee. PAPR reduction of OFDM signals using a reduced complexity PTS technique. Signal Processing Letters, IEEE.2004,11(11):887-890
[16]S. H. Han, J. H. Lee. An overview of peak-to-average power ratio reduction techniques for multicarrier transmission. Wireless Communications, IEEE.2005,12(2):56-65
[17]M. Ghogho, A. Swami, G. B. Giannakis. Optimized null-subcarrier selection for CFO estimation in OFDM over frequency-selective fading channels. Global Telecommunications Conference,2001. GLOBECOM'01. IEEE,2001:202-206
[18]X. Ma, C. Tepedelenlioglu, G. B. Giannakis, et al. Non-data-aided carrier offset estimators for OFDM with null subcarriers:identifiability, algorithms, and performance. Selected Areas in Communications, IEEE Journal on.2001,19(12): 2504-2515
[19]K. Sathananthan, C. Tellambura. Probability of error calculation of OFDM systems with frequency offset. Communications, IEEE Transactions on.2001,49(11): 1884-1888
[20]B. Chen, H. Wang. Blind estimation of OFDM carrier frequency offset via oversampling. Signal Processing, IEEE Transactions on.2004,52(7):2047-2057
[21]D. Falconer, S. L. Ariyavisitakul, A. Benyamin-Seeyar, et al. Frequency domain equalization for single-carrier broadband wireless systems. Communications Magazine, IEEE.2002,40(4):58-66
[22]A. Gusmao, R. Dinis, N. Esteves. On frequency-domain equalization and diversity combining for broadband wireless communications. Communications, IEEE Transactions on.2003,51(7):1029-1033
[23]Y. Wang, X. Dong. Comparison of frequency offset and timing offset effects on the performance of SC-FDE and OFDM over UWB channels. Vehicular Technology, IEEE Transactions on.2009,58(1):242-250
[24]H. G. Myung. Technical overview of 3GPP LTE. Polytechnic University of New York. 2008
[25]Q. Li, G. Li, W. Lee, et al. MIMO techniques in WiMAX and LTE:a feature overview. Communications Magazine, IEEE.2010,48(5):86-92
[26]G. Charalabopoulos, P. Stavroulakis, A. H. Aghvami. Pre-post-and balanced equalization in OFDM. Vehicular Technology Conference,2003. VTC 2003-Fall.2003 IEEE 58th,2003:3145-3148
[27]R. L. U. Choi, R. D. Murch. Frequency domain pre-equalization with transmit diversity for MISO broadband wireless communications. Vehicular Technology Conference,2002. Proceedings. VTC 2002-Fall.2002 IEEE 56th,2002:1787-1791
[28]D. Huaiyu, A. F. Molisch, H. V. Poor. Downlink capacity of interference-limited MIMO systems with joint detection. Wireless Communications, IEEE Transactions on. 2004,3(2):442-453
[29]A. Burg, M. Borgmann, C. Simon, et al. Performance tradeoffs in the VLSI implementation of the sphere decoding algorithm.3G Mobile Communication Technologies,2004.3G 2004. Fifth IEE International Conference on,2004:93-97
[30]C. Wan, J. G. Andrews. The Capacity Gain from Base Station Cooperative Scheduling in a MIMO DPC Cellular System. Information Theory,2006 IEEE International Symposium on,2006:1224-1228
[31]A. Tolli, H. Pennanen, P. Komulainen. On the Value of Coherent and Coordinated Multi-Cell Transmission. Communications Workshops,2009. ICC Workshops 2009. IEEE International Conference on,2009:1-5
[32]S. A. Jafar, A. J. Goldsmith. Transmitter optimization for multiple antenna cellular systems. Information Theory,2002. Proceedings.2002 IEEE International Symposium on,2002:50
[33]A. A. M. Saleh, A. Rustako, R. Roman. Distributed Antennas for Indoor Radio Communications. Communications, IEEE Transactions on.1987,35(12):1245-1251
[34]C. Wan, J. G. Andrews. Downlink performance and capacity of distributed antenna systems in a multicell environment. Wireless Communications, IEEE Transactions on. 2007,6(1):69-73
[35]P. Marsch, G. Fettweis. A Framework for Optimizing the Uplink Performance of Distributed Antenna Systems under a Constrained Backhaul. Communications,2007. ICC'07. IEEE International Conference on,2007:975-979
[36]S. Shamai, B. M. Zaidel. Enhancing the cellular downlink capacity via co-processing at the transmitting end. Vehicular Technology Conference,2001. VTC 2001 Spring. IEEE VTS 53rd,2001:1745-1749
[37]O. Somekh, O. Simeone, Y. Bar-Ness, et al. CTH11-2:Distributed Multi-Cell Zero-Forcing Beamforming in Cellular Downlink Channels. Global Telecommunications Conference,2006. GLOBECOM'06. IEEE,2006:1-6
[38]O. Somekh, B. M. Zaidel, S. Shamai. Sum Rate Characterization of Joint Multiple Cell-Site Processing. Information Theory, IEEE Transactions on.2007,53(12): 4473.4497
[39]A. Stefanov, E. Erkip. Cooperative coding for wireless networks. Communications, IEEE Transactions on.2004,52(9):1470-1476
[40]T. Cover, A. E. L. Gamal. Capacity theorems for the relay channel. Information Theory, IEEE Transactions on.1979,25(5):572-584
[41]A. Sendonaris, E. Erkip, B. Aazhang. User cooperation diversity. Part Ⅰ. System description. Communications, IEEE Transactions on.2003,51(11):1927-1938
[42]A. Sendonaris, E. Erkip, B. Aazhang. User cooperation diversity. Part Ⅱ. Implementation aspects and performance analysis. Communications, IEEE Transactions on.2003,51(11):1939-1948
[43]M. Janani, A. Hedayat, T. E. Hunter, et al. Coded cooperation in wireless communications:space-time transmission and iterative decoding. Signal Processing, IEEE Transactions on.2004,52(2):362-371
[44]Q. Zhao, H. Li. Performance of differential modulation with wireless relays in Rayleigh fading channels. Communications Letters, IEEE.2005,9(4):343-345
[45]T. Himsoon, W. Su, K. J. R. Liu. Differential transmission for amplify-and-forward cooperative communications. Signal Processing Letters, IEEE.2005,12(9):597-600
[46]D. Chen, J. N. Laneman. Cooperative diversity for wireless fading channels without channel state information. Signals, Systems and Computers,2004. Conference Record of the Thirty-Eighth Asilomar Conference on,2004:1307-1312
[47]A. Wittneben, I. Hammerstrom. Multiuser zero forcing relaying with noisy channel state information [wireless ad hoc network applications]. Wireless Communications and Networking Conference,2005 IEEE,2005:1018-1023
[48]Z. Jian, M. Kuhn, A. Wittneben, et al. Cooperative Transmission Schemes for Decode-and-Forward Relaying. Personal, Indoor and Mobile Radio Communications, 2007. PIMRC 2007. IEEE 18th International Symposium on,2007:1-5
[49]N. Devroye, N. B. Mehta, A. F. Molisch. Asymmetric Cooperation Among Relays with Linear Precoding. Global Telecommunications Conference,2007. GLOBECOM'07. IEEE,2007:4391-4396
[50]G. Atia, A. F. Molisch. Cooperative Relaying with Imperfect Channel State Information. Global Telecommunications Conference,2008. IEEE GLOBECOM 2008. IEEE,2008: 1-6
[51]L. Hang, W. Fangxiang, K. Jinghua, et al. Multi-User Precoding and Energy-Efficient Relaying Scheme in Multi-Relay Systems. Communications Workshops (ICC),2011 IEEE International Conference on,2011:1-5
[52]A. Sanderovich, O. Somekh, S. Shamai. Uplink Macro Diversity with Limited Backhaul Capacity. Information Theory,2007. ISIT 2007. IEEE International Symposium on,2007:11-15
[53]L. Falconetti, C. Hoymann, R. Gupta. Distributed Uplink Macro Diversity for Cooperating Base Stations. Communications Workshops,2009. ICC Workshops 2009. IEEE International Conference on,2009:1-5
[54]H. Zhang, H. Dai, Q. Zhou. Base station cooperation for multiuser MIMO:Joint transmission and BS selection. Conference on information sciences and systems,2004
[55]H. Zhang, H. Dai. Cochannel interference mitigation and cooperative processing in downlink multicell multiuser MIMO networks. EURASIP Journal on Wireless Communications and Networking.2004,2004(2):222-235
[56]H. Weingarten, Y. Steinberg, S. Shamai. The capacity region of the Gaussian multiple-input multiple-output broadcast channel. Information Theory, IEEE Transactions on.2006,52(9):3936-3964
[57]T. Yoo, A. Goldsmith. Optimality of zero-forcing beamforming with multiuser diversity. Communications,2005. ICC 2005.2005 IEEE International Conference on,2005: 542-546
[58]U. Erez, S. Shamai, R. Zamir. Capacity and lattice strategies for canceling known interference. Information Theory, IEEE Transactions on.2005,51(11):3820-3833
[59]M. Vemula, D. Avidor, J. Ling, et al. Inter-cell coordination, opportunistic beamforming and scheduling. Communications,2006. ICC'06. IEEE International Conference on,2006:5319-5324
[60]B. Song, R. L. Cruz, B. D. Rao. Network duality for multiuser MIMO beamforming networks and applications. Communications, IEEE Transactions on.2007,55(3): 618-630
[61]L. Venturino, N. Prasad, X. Wang. Coordinated linear beamforming in downlink multi-cell wireless networks. Wireless Communications, IEEE Transactions on.2010, 9(4):1451-1461
[62]V. R. Cadambe, S. A. Jafar. Interference Alignment and Degrees of Freedom of the K-User Interference Channel. Information Theory, IEEE Transactions on.2008,54(8): 3425-3441
[63]K. Gomadam, V. R. Cadambe, S. A. Jafar. Approaching the capacity of wireless networks through distributed interference alignment. Global Telecommunications Conference,2008. IEEE GLOBECOM 2008. IEEE,2008:1-6
[64]R. Tresch, M. Guillaud. Cellular interference alignment with imperfect channel knowledge. Communications Workshops,2009. ICC Workshops 2009. IEEE International Conference on,2009:1-5
[65]B. M. Hochwald, T. L. Marzetta. Unitary space-time modulation for multiple-antenna communications in Rayleigh flat fading. Information Theory, IEEE Transactions on. 2000,46(2):543-564
[66]B. L. Hughes. Differential space-time modulation. Information Theory, IEEE Transactions on.2000,46(7):2567-2578
[67]B. M. Hochwald, W. Sweldens. Differential unitary space-time modulation. Communications, IEEE Transactions on.2000,48(12):2041-2052
[68]C. Shan, A. Nallanathan, P. Y. Kam. A new class of signal constellations for differential unitary space-time modulation (DUSTM). Communications Letters, IEEE.2004,8(1): 1-3
[69]M. Hajiaghayi, C. Tellambura. Unitary signal constellations for differential space-time modulation. Communications Letters, IEEE.2007,11(1):25-27
[70]J. Wang, M. K. Simon, K. Yao. On the optimum design of differential unitary space-time modulation. Global Telecommunications Conference,2003. GLOBECOM'03. IEEE,2003:1968-1972
[71]Q. Zhao, H. Li. Differential modulation for cooperative wireless systems. Signal Processing, IEEE Transactions on.2007,55(5):2273-2283
[72]T. Wang, Y. Yao, G. B. Giannakis. Non-coherent distributed space-time processing for multiuser cooperative transmissions. Wireless Communications, IEEE Transactions on. 2006,5(12):3339-3343
[73]G. B. Giannakis, C. Tepedelenlioglu. Basis expansion models and diversity techniques for blind identification and equalization of time-varying channels. Proceedings of the IEEE.1998,86(10):1969-1986
[74]G. B. Giannakis, X. Ma, G. Leus, et al. Space-time-Doppler coding over time-selective fading channels with maximum diversity and coding gains. Acoustics, Speech, and Signal Processing (ICASSP),2002 IEEE International Conference on,2002: III-2217-III-2220
[75]X. Ma, G. B. Giannakis. Maximum-diversity transmissions over doubly selective wireless channels. Information Theory, IEEE Transactions on.2003,49(7):1832-1840
[76]X. Ma, G. B. Giannakis, S. Ohno. Optimal training for block transmissions over doubly selective wireless fading channels. Signal Processing, IEEE Transactions on.2003, 51(5):1351-1366
[77]X. Ma, G. B. Giannakis. Space-time-multipath coding using digital phase sweeping or circular delay diversity. Signal Processing, IEEE Transactions on.2005,53(3): 1121-1131
[78]L. Rugini, P. Banelli. BER of OFDM systems impaired by carrier frequency offset in multipath fading channels. Wireless Communications, IEEE Transactions on.2005, 4(5):2279-2288
[79]J. P. C. L. Miranda, H. M. d. Oliveira. On Galois-division multiple access systems: figures of merit and performance evaluation. XIX Simposio Brasileiro de Telecommunication, Fortaleza CE.2001
[80]H. M. d. Oliveira, J. P. C. L. Miranda, R. M. C. d. Souza. Spread spectrum based on finite field Fourier transforms. ICSECIT 2001 International Conference on Systems Engineering, Communications and Information Technologies, Punta Arenas, Chile. Apr. 2001
[81]F. Fekri, D. B. Williams. Multicarrier modulation via finite-field transforms. Digital Signal Processing Workshop,2002 and the 2nd Signal Processing Education Workshop. Proceedings of 2002 IEEE 10th,2002:16-19
[82]R. M. C. De Souza, H. De Oliveira, A. Kauffman, et al. The Hartley transform in a finite field. Revista da Sociedade Brasileira de Telecomunicacoes.1999,14(1):46-54
[83]R. N. Bracewell. Discrete hartley transform. JOSA.1983,73(12):1832-1835
[84]J. Hong, M. Vetterli. Hartley transforms over finite fields. Information Theory, IEEE Transactions on.1993,39(5):1628-1638
[85]J. Hong, M. Vetterli, P. Duhamel. Basefield transforms with the convolution property. Proceedings of the IEEE.1994,82(3):400-412
[86]J. Miranda, H. De Oliveira. On Galois-Division Multiple Access Systems:Figures of Merit and Performance Evaluation. Anais do 19o Simposio Brasileiro de Telecomunicacoes, Fortaleza CE.2001
[87]C. Windpassinger, Detection and precoding for multiple input multiple output channels: Shaker,2004
[88]D. Divsalar, M. K. Simon. The design of trellis coded MPSK for fading channels: Performance criteria. Communications, IEEE Transactions on.1988,36(9):1004-1012
[89]V. Tarokh, N. Seshadri, A. R. Calderbank. Space-time codes for high data rate wireless communication:Performance criterion and code construction. Information Theory, IEEE Transactions on.1998,44(2):744-765
[90]G. H. Golub, C. F. Van Loan, Matrix computations vol.3:Johns Hopkins University Press,1996
[91]C. Tepedelenlioglu. Maximum multipath diversity with linear equalization in precoded OFDM systems. Information Theory, IEEE Transactions on.2004,50(1):232-235
[92]T. Pollet, M. Van Bladel, M. Moeneclaey. BER sensitivity of OFDM systems to carrier frequency offset and Wiener phase noise. Communications, IEEE Transactions on. 1995,43(234):191-193
[93]J. N. Laneman, D. N. C. Tse, G. W. Wornell. Cooperative diversity in wireless networks:Efficient protocols and outage behavior. Information Theory, IEEE Transactions on.2004,50(12):3062-3080
[94]S. Gollakota, S. D. Perli, D. Katabi. Interference alignment and cancellation. ACM SIGCOMM Computer Communication Review,2009:159-170
[95]B. Ozdemir, O. Gurbuz. Scheduling approach for MIMO with Tomlinson-Harashima precoding. Vehicular Technology Conference,2006. VTC 2006-Spring. IEEE 63rd, 2006:329-333
[96]R. A. Horn, C. R. Johnson, Matrix analysis:Cambridge university press,1990
[97]H. Long, F. Wang, J. Kuang, et al. Multi-User Precoding and Energy-Efficient Relaying Scheme in Multi-Relay Systems. Communications Workshops (ICC),2011 IEEE International Conference on,2011:1-5
[98]H. Meghdadi, J. P. Cances. Performance analysis of a cooperative multiple access relaying scheme. Proceedings of the 6th International Wireless Communications and Mobile Computing Conference,2010:1065-1069
[99]T. D. Nguyen, O. Berder, O. Sentieys. Impact of transmission synchronization error and cooperative reception techniques on the performance of cooperative MIMO systems. Communications,2008. ICC'08. IEEE International Conference on,2008: 4601-4605
[100]C. Suh, D. Tse. Interference alignment for cellular networks. Communication, Control, and Computing,2008 46th Annual Allerton Conference on,2008:1037-1044
[101]W. Shin, N. Lee, J. B. Lim, et al. On the design of interference alignment scheme for two-cell MIMO interfering broadcast channels. Wireless Communications, IEEE Transactions on.2011,10(2):437-442
[102]B. Zhuang, R. A. Berry, M. L. Honig. Interference alignment in MIMO cellular networks. Acoustics, Speech and Signal Processing (ICASSP),2011 IEEE International Conference on,2011:3356-3359
[103]A. Mathal, P. Moschopoulos. A form of multivariate gamma distribution. Annals of the Institute of Statistical Mathematics.1992,44(1):97-106
[104]D. Liu, Q. Zhang, Q. Chen. Structures and performance of noncoherent receivers for unitary space-time modulation on correlated fast-fading channels. Vehicular Technology, IEEE Transactions on.2004,53(4):1116-1125
[105]B. M. Hochwald, T. L. Marzetta, T. J. Richardson, et al. Systematic design of unitary space-time constellations. Information Theory, IEEE Transactions on.2000,46(6): 1962-1973
[106]W. Jakes, Mobile radio propagation:Wiley-IEEE Press,2009
[107]J. Ziyan, S. Handa, F. Sasamori, et al. Multiple-symbol differential detection for unitary space-time-frequency coding. IEICE transactions on communications.2010, 93(1):90-98
[108]E. U. T. R. Access. Physical Channels and Modulation.3GPP TS.2009,36:V8
[109]M. Qingyu, W. Wenbo, Y. Dacheng, et al. An Investigation of Inter-cell Interference in UTRA-TDD system. Vehicular Technology Conference,2000. IEEE VTS-Fall VTC 2000.52nd,2000:3002-3007
[110]L. Zheng, D. N. C. Tse. Diversity and multiplexing:A fundamental tradeoff in multiple-antenna channels. Information Theory, IEEE Transactions on.2003,49(5): 1073-1096
[111]X. Ma, G. B. Giannakis. Maximum-diversity transmissions over time-selective wireless channels. Wireless Communications and Networking Conference,2002. WCNC2002. 2002 IEEE,2002:497-501
[112]Q. Guo, L. Ping, D. Huang. A low-complexity iterative channel estimation and detection technique for doubly selective channels. Wireless Communications, IEEE Transactions on.2009,8(8):4340-4349
[113]J. J. Van de Beek, O. Edfors, M. Sandell, et al. On channel estimation in OFDM systems. Vehicular Technology Conference,1995 IEEE 45th,1995:815-819
[114]I. Barhumi, G. Leus, M. Moonen. Optimal training design for MIMO OFDM systems in mobile wireless channels. Signal Processing, IEEE Transactions on.2003,51(6): 1615-1624
[115]R. Xu, F. C. M. Lau. Performance analysis for MIMO systems using zero forcing detector over Rice fading channel. Circuits and Systems,2005. ISCAS 2005. IEEE International Symposium on,2005:4955-4958
[116]W. Tan, R. Gupta. On approximating the non-central Wishart distribution with Wishart distribution. Commun. Stat. Theory Method.1983,12(22):2589-2600
[117]D. Maiwald, D. Kraus. On moments of complex Wishart and complex inverse Wishart distributed matrices. Acoustics, Speech, and Signal Processing,1997. ICASSP-97., 1997 IEEE International Conference on,1997:3817-3820
[118]T. L. Tung, K. Yao, R. Hudson. Channel estimation and adaptive power allocation for performance and capacity improvement of multiple-antenna OFDM systems. Wireless Communications,2001.(SPAWC'01).2001 IEEE Third Workshop on Signal Processing Advances in,2001:82-85
[119]Universal mobile telecommunications system (UMTS); Spacial channel model for multiple input multiple output (MIMO) simulations (3GPP TR 25.996 version 8.0.0 Release 8),3GPP Std, ed:TR Patent 125996V8