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  • 學位論文

多載波無線通訊系統之設計與分析

DESIGN AND ANALYSIS OF MULTI-CARRIER WIRELESS SYSTEMS

指導教授 : 陳博現
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摘要


高速資料傳輸不僅被noise限制傳輸速率,尤其甚者,由於通道記憶特性所產生之ISI更是造成高速資料傳輸系統效能不彰的主要因素。除了傳統上使用Equalizer來抑制ISI外, 多載波(Multiple carrier)技術或正交分頻多工系統(Orthogonal Frequency Division Multiplexing, OFDM)技術被廣泛的應用在寬頻無線通訊系統,其抗多路徑衰減等優良特性,為DAB、DVB與無線區域網路(802.11a/g) 等標準所採用。此外近年來,為提昇system capacity與頻譜使用效率,Multiple input multiple output (MIMO) 系統效能的研究亦成為學術界之顯學;不僅學界如此,工業界也投注大量資源研發,對此技術多有著墨。總括來說,結合多載波(Multiple carrier)技術與Multiple input multiple output (MIMO) 技術的MIMO-OFDM技術已被公認為下一代寬頻無線高速資料傳輸系統重要的candidates之一,此外MIMO-OFDM技術因具有高頻譜效率、抗多路徑衰減等特性,目前在工業界為寬頻無線固接/行動系統(Metro. Broadband Wireless Access Network、802.16d/e)及無線區域網路(802.11n、HiperLAN/2)等標準所採用。本論文針對多載波(Multiple carrier)技術與Multiple input multiple output (MIMO) 技術,分別應用於MC-CDMA接收機設計、效能分析及低複雜度channel feedback coding scheme。 此篇論文分析在MC-CDMA的上傳(Uplink, UL)系統上設計最佳(optimal)多用戶偵測接收機 (Multi-user Detector, MUD)並利用Belief propagation (BP)技術來做效能分析,此外為使channel model更實用,我們亦考量channel mismatch效應。利用Belief propagation技術我們設計出一iterative optimal MUD,不僅效能分析上與replica method的理論結果完全吻合,其實現複雜度遠低於傳統的optimal MUD (複雜度與使用者個數成指數成長) ,只與使用者個數平方成正比,也就是說,此BP-based iterative optimal MUD的實現複雜度約與Linear MUD相當。此篇論文亦設計一極有效率的Channel State Information (CSI) feedback的機制應用於 MIMO-OFDM系統上;我們提出利用QRD的分解方式來分解MIMO channel matrix以取代SVD,此種方法在非對稱的multiple antenna array configuration下的效能幾乎與SVD-based vector coding scheme相當,但複雜度卻遠低於SVD。此外我們亦提出一interpolation scheme,不但讓回傳的CSI大幅下降,也能繼續維持precoder的正交性。 最後本論文針對 OFDM 在天線陣列上達成平行頻道問題提出全新的低複雜度多用戶空間-頻率編碼排程技術 (Multi-user Space-Frequency Coding Scheme、MU-SFCS scheduling),我們考慮在無線通道下採用空間-時間編碼技術並應用於多用戶MIMO (Multi-input Multi-output)系統以獲得multiuser diversity。可事先identify通道結構,再透過使用傳送端Precoder與極有效率的排程演算法設計出之少量空間軸傅氏基底向量來實現低複雜度的 SDMA (Spatial Division Multiple Access),而獲致極大的系統容量。我們利用在空間通道上採用傅利葉轉換於MIMO通道以獲得angle-domain資訊,使得每位使用者所看到的空間通道結構可被identify出來,因而定義出每位使用者所需要的空間平行頻道,而payload data便可透過這些各別使用者所喜愛的空間平行頻道來傳送與接收進而提升系統容量。簡言之,我們使用的策略包括1) 在傳送端設計Precoder,利用空間軸傅氏基底向量當作spatial codeword。2) 利用training period在不同時間傳送不同的空間軸傅氏基底向量,以達成Switched beamforming 效果。3)接收端利用training period時所送來的spatial codeword來追蹤空間-時間無線頻道結構,以找出最佳的angle-frequency組合。4)在傳送端採用極有效率的排程演算法。

並列摘要


High data rate communications are limited not only by noise but also by inter-symbol interference (ISI) due to the memory of the dispersive wireless communication channel. Except the conventional channel equalization techniques are used to suppress the ISI caused by channel, an multi-carrier approach, e.g., orthogonal frequency division multiplexing (OFDM), towards transmitting data over a multipath channel also allow us to design a system supporting high data rate. Combining OFDM transmissions with code division multiple access (CDMA) exploit the wideband channel’s inherent frequency diversity by spreading each symbol across multiple sub-carriers. The combination has two major advantages. One is its own capability to lower the symbol rate in each subcarrier enough to have a quasi-synchronous signal reception in uplink. The other is that it can effectively combine the energy of the received signal scattered in the frequency domain. That is, it is possible to prevent the obliteration of certain sub-carriers by deep frequency domain fades. This is achieved by spreading each sub-carrier’s signal with the aid of a spreading code and thereby increasing the achievable error-resilience. In this thesis, we analyze the bit-error-rate (BER) performance of the optimum multiuser detection (MUD) with channel mismatch in multi-carrier code-division-multiple-access (MC-CDMA) systems. However, it is NP-hard to implement an optimum MUD algorithm. To justify the BER performance and to make the optimum MUD feasible, based on Pearl’s belief propagation (BP) scheme, we put together a low-complexity iterative MUD algorithm for MC-CDMA systems. On the other hand, systems that employ multiple antennas in both the transmitter and the receiver of a wireless system have been shown to promise extraordinary spectral efficiency. One way to realize the enormous throughput is to exploit the spatial multiplexing (SM) gain by transmitting several data streams across the wireless MIMO channel simultaneously. Unfortunately, an SM system is sensitive to the rank of its MIMO channel matrix. To prevent ill-conditioned MIMO channel matrix from affecting the system data throughput, e.g., in the downlink scenarios where the number of the transmit antennas is larger than the number of the receive antennas and the corresponding MIMO channel matrix has a non-empty null space, a transmit spatial pre-filtering scheme should be designed to feed the simultaneously-transmitted data streams into the signal space of the MIMO channel matrix, instead of wasting the transmit power in the null space of the MIMO channel matrix. However, the efficiency of the spatial pre-filtering scheme highly depends on the availability of the MIMO channel state information (CSI), which can be estimated at the receiver. Therefore, feedback of sufficiently reliable CSI from the receiver to the transmitter is crucial, especially in the downlink scenarios. Hence, in this thesis, we also focus on the development of efficient coding schemes for channel feedback in downlink scenario, which expects a higher data throughput and is considered the bottleneck in a MIMO system. The thesis contains Four results. First, we analyze the bit-error-rate (BER) performance of the optimum multiuser detection (MUD) with channel mismatch in MC-CDMA systems. To justify the BER performance and to make the optimum MUD feasible, based on Pearl’s belief propagation (BP) scheme, we put together a low-complexity iterative MUD algorithm for MC-CDMA systems. Furthermore, channel mismatch is introduced into the BP-based MUD algorithm to make the scenario general. With channel mismatch, the analytical results of the BP-based MUD algorithm conform perfectly to, and the simulation results of the BP-based MUD algorithm conform very closely to the BER performance of the optimum MUD derived using the replica method, which is a non-trivial extension of the existing replica approach mentioned above. Without channel mismatch, the problem becomes a special case of our contribution. Second, Raleigh and Cioffi proposed a singular-value-decomposition based space-time architecture for multiple-input-multiple-output (MIMO) wireless systems using antenna arrays, discrete matrix multi-tone (DMMT) coding scheme, which claims to achieve near-optimum performance in both signal diversity and channel capacity. However, the DMMT coding scheme suffers high computational complexity in non-stationary channel environments, where channel information update is frequently needed at both the transmitter and the receiver. In addition, the transmitter may need to rely on a wideband feedback channel to obtain the entire set of vector channel information, which is obviously impractical. By exploring the MIMO channel structures, we develop an adaptive version of the DMMT coding scheme for a high-capacity MIMO system with time-varying frequency-selective channels. In the proposed coding scheme, a lowv complexity Jacobi-SVD is utilized to iteratively optimize the transmit signaling by tracking merely the dominant fading paths in the MIMO wireless channel, while only very little feedback information is required. An analytic capacity lower bound considering channel-tracking errors is derived for systems employing the proposed coding scheme. Simulation results reconfirm that the proposed coding scheme works efficiently in indoor wireless applications. Third, for MIMO-OFDM wireless systems, gain in channel throughput educed through sufficient feedback of the CSI is significant, particularly when the number of transmit antennas is larger than the number of receive antennas. In this part, we demonstrate that, in such scenarios, 1) the CSI of each OFDM sub-carrier can be parameterized into a short bit stream by a proposed low-complexity QR decomposition on the corresponding MIMO channel matrix, 2) the overall CSI can be reliably represented by a proposed parameter interpolation on the above bit streams of only a fraction of sub-carriers, and 3) a MIMO-OFDM system with a low-rate CSI feedback parameterized above can provide a channel throughput comparable to the channel capacity. Finally, we propose a novel scheduling mechanism to enhance the throughput in a multiuser MIMO system. As it is known, based on the information theory, that a wireless system with antenna array at both sides of a communication link is able to achieve excellent spectral efficiency. For multiuser multiple-input-multiple-output(MU-MIMO) services, orthogonal multiple accesses, e.g., frequency division multiple access (FDMA) and time division multiple access (TDMA) are popular options to avoid multiuser interference. However, for the FDMA (or TDMA) system, the spatial resources of a frequency band (or time slot) are consumed by a single user. The spatial utility of such a system is very low if it happens to have a common clustered channel structure. A high sum-rate is achievable in an MU-MIMO system where a common frequency or time resource is shared by multiple users if transmitters assume perfect knowledge of the corresponding channels. However, in order to reach this capacity, existing coding schemes suffer not only from high computational complexity but also from the need for excess channel state information (CSI) feedback. It is shown in the previous work that the ergodic capacity of a system employing the simple multiuser angle-frequency coding scheme is close to that of a system employing dirty paper coding but significantly better than that of an orthogonal multiplexing system. In this part of thesis, we focus on the scheduling mechanism for angle-frequency subchannels. With the channel identification, we propose two efficient scheduling strategies to make MU transmit simultaneously without serious packet collisions. With the proposed approaches, the packets transmitted to different subscriber units can be scheduled efficiently at the access point to increase the channel utilization and decrease the average packet delay.

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