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published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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多輸入多輸出傳輸在過去二十多年來無線通信研究中一直處於中心地位。人們對信息需求的爆炸性增長導致大規模多輸入多輸出系統的出現與發展。在大規模多輸入多輸出系統中有幾十甚至上百的天線與用戶。這種大規模天線能夠極大地提高系統容量及對噪聲的魯棒性。然而，大規模天線系統的物理實現卻是十分困難的。一方面，最優的信號處理算法通常需要指數增長的複雜度。另一方面，數目繁多的天線意味大量包括功率放大器和數模轉換器在內的硬件開銷。這篇論文的研究重點在於能夠降低信號處理複雜度和硬件開銷的信號檢測和預編碼算法。具體而言，本論文的研究包括三部分： / 在第一部分中，我們考慮多輸入多輸出系統中的一個基本問題信號檢測。格型解碼是信號檢測中的一種傳統方法。但是格型解碼（以及其快速近似算法格基規約輔助算法)放鬆了信號檢測中的符號邊界約束因而受到性能限制。我們提出一種自適應的正則化方法來避免格型解碼中邊界約束鬆弛帶來的負面影響。這種方法是基於最大似然解碼器的拉格朗日對偶鬆弛。我們發現了格型解碼和最大似然解碼的一個十分有趣的關係，而這個關係在現有的文獻中並沒有被提及。數值仿真結果顯示拉格朗日對偶鬆弛方法比現有的格型解碼更為優勝。 / 在第二部分中，我們考慮多用戶信號廣播中的矢量擾動方法。矢量擾動是一種能夠接近信道總容量以及簡化用戶數據處理方法。然而，傳統的矢量擾動會導致每根傳輸天線上都有相當大的功率， 導致天線模擬前端的硬件實現有相當大的難度。我們提出一種每天線功率受限的矢量擾動方法來解決這個問題。在這個方法中，我們需要解決一個整數規劃問題。然而，求解這個整數規劃問題需要用到複雜度十分高的枚舉算法。我們用拉格朗日對偶鬆弛方法把這個整數規劃轉化為標準的整數最小二乘問題，然後採用快速的近似算法來求解。數值仿真顯示提出的方法能夠顯著地降低高每天線功率造成的功率回饋。 / 在最後一部分，我們考慮單用戶通信中的恆定包絡預編碼。恆定包絡預編碼是一種最近被提出用於超大規模多輸入多輸出系統的方法。恆定包絡預編碼的優點在於能夠利用價格低廉但是功率效率高的功率放大器。但是恆定包絡預編碼中的一些信號處理問題在之前的文獻中只是得到了部分解答。我們為這些信號處理問題提供了一個完整的解決方案。更進一步地，我們用天線子集選擇來加強恆定包絡預編碼以優化天線傳輸信號及進一步降低天線成本。數值仿真結果顯示包絡預編碼的性能只稍遜於傳統的波束成型方法，但是能恆定包絡傳輸和降低活動的天線數目。 / Multiple-input multiple-output (MIMO) transmission has been at the core of wireless communication research for the past two decades. Driven by the explosive increase of data demand, the development of MIMO systems has entered a large-scale realm where there are dozens of or even more than a hundred antennas and users. The large number of antennas can significantly boost the system throughput and robustness against noise. However, the physical realization of such a large MIMO system can be very complicated and expensive. On the one hand, optimal signal processing algorithms usually have complexities that increase rapidly in the numbers of antennas and users. On the other hand, large number of antennas means increased hardware overheads, such as those of power amplifiers and D/A converters. This thesis considers efficient precoding and detection algorithms that can reduce implementation complexity and cost. Specifically, the thesis consists of the following three parts: / In the first part, we consider a fundamental problem in MIMO communication, namely MIMO detection. The traditional lattice decoding methods, as well as its efficient approximations by lattice reduction aided (LRA) methods, relax the symbol bounds in detection and thus suffer from performance loss. We propose a systematic adaptive regularization approach to lattice decoding to alleviate the adverse effect of symbol bound relaxation, which is based on the study of a Lagrangian dual relaxation (LDR) of the optimal maximum-likelihood (ML) detector. We find an intriguing relationship between lattice decoding and ML, which was not reported in the previous literature. Simulation results show that the proposed LDR approach can significantly outperform existing lattice decoding and LRA methods. / In the second part, we consider the vector perturbation approach which is a promising technique to achieve near-sum capacity and allows simple user processing in the multiuser multiple-input single-output (MISO) downlink scenario. However, the conventional vector perturbation designs can have very high perantenna powers, which causes significant difficulty to power amplifier implementations. To tackle this problem, we propose a vector perturbation design with per-antenna power constraints (VP-PAPC). The resulting optimization problem is an integer program which requires a computationally demanding enumeration process. Lagrangian dual relaxation is used to transform the VP-PAPC problem into standard integer least square problems which may have efficient approximations. Simulation results show that the proposed method can effectively reduce the power back-off caused by high per-antenna power in conventional vector perturbation. / In the last part, we consider constant envelope (CE) precoding in the singleuser MISO downlink scenario. CE precoding is recently proposed as a mean to utilize cheap but power-efficient power amplifiers in very large MIMO systems. We provide complete solutions to some fundamental signal processing issues in CE precoding which were only partially solved in the previous literature. In addition, we enhance CE precoding with antenna subset selection for transmit optimization and implementation cost reduction. Simulation results reveal that the proposed method only exhibits moderate power loss compared to non-CE beamforming but have the advantages of CE transmission and fewer active transmitting antennas. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Pan, Jiaxian. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 135-147). / Abstracts also in Chinese.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--Drexel University, 2006. / Includes abstract and vita. Includes bibliographical references (leaves 76-78).

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We propose a linear mean square error channel estimator that exploits the joint space-time-frequency (STF) correlations of the wireless fading channel for applications in multiple-antenna orthogonal frequency division multiplexing systems. Our work generalizes existing channel estimators to the full dimensions including transmit spatial, receive spatial, time, and frequency. This allows versatile applications of our STF channel estimator to any fading environment, ranging from spatially-uncorrelated slow-varying frequency-flat channels to spatially-correlated fast-varying frequency-selective channels. / The proposed STF channel estimator reduces to a time-frequency (TF) channel estimator when no spatial correlations exist. In another perspective, the lower-dimension TF channel estimator can be viewed as an STF channel estimator with spatial correlation mismatch for space-time-frequency selective channels. / Computer simulations were performed to study the mean-square-error (MSE) behavior with different pilot parameters. We then evaluate the suitability of our STF channel estimator on a space-frequency block coded OFDM system. Bit error rate (BER) performance degradation, with respect to perfect coherent detection, is limited to less than 2 dB at a BER of 10-5 in the modified 3GPP fast-fading suburban macro environment. Modifications to the 3GPP channel involves reducing the base station angle spread to imitate a high transmit spatial correlation scenario to emphasize the benefit of exploiting spatial correlation in our STF channel estimator.