IEEE 802.16e OFDM上行及OFDMA下行通道估測技術與數位信號處理器實現之探討

Abstract

在過去數年間，多載波調變 (multicarrier modulation)，尤其是正交分頻多工 (OFDM) 技術已經應用在許多數位通訊應用中。採用OFDM一個最主要的原因是增加抗頻率選擇性衰變及窄頻干擾的能力。在單一載波的系統中，衰變或干擾可能會導致整個連結失效；但在一個多載波的系統，僅僅只有一小部分的載波會受到影響。我們聚焦在IEEE 802.16e OFDM上行及OFDMA下行的部分，並用數位信號處理器去實現通道估測的機制。此數位訊號處理器的環境是Innovative Integration公司的Quixote個人電腦插板，其上裝置為德州儀器公司的TMS320C6416，是個擁有強大數學運算功能的處理器。 通道估測大致可以分成兩個階段。首先我們使用最小平方差的估測器來估計在導訊上的通道頻率響應，這是為了硬體的計算方便。而內插的方法我們則研究了多項式內插法及Cubic Spline內插法；而在用時域的資料改善的方法有下列三種：二維內插法、最小平方法(Least Squares)以及最小平均平方差適應 (Normalized LMS adaptation）；最後我們將通道估測與信號偵測何在一起作已達到更好的效果(Joint Channel Estimation and Symbol Detection)。我們先在AWGN通道上驗證我們的模擬模型，然後在分別在靜態及時變的Rayleigh通道上模擬。 至於數位信號處理器實現的部份，考量其運算複雜度，只用簡單的內插法綜合二維內插。為了增進程式的執行效率，我們先將原始的浮點運算C程式版本修改為實數運算的程式版本，接著再考慮數位訊號處理器的特性來修改之前的程式 在本篇論文中，我們首先簡介IEEE 802.16e OFD上行及OFDMA下行的標準及機制。接著，我們介紹所用通道估測的技巧和DSP的實現環境。最後，我們描述各種通道估測技術的效果及數位訊號處理器實現方面的實驗結果。

Multicarrier modulation, in particular orthogonal frequency division multiplexing (OFDM), has been successfully applied to a wide variety of digital communications applications over the past several years. One of the main reason to use OFDM is to increase the robustness against frequency selective fading and narrowband interference. In a single carrier system, a single fade or interference can cause the entire link to fail, but in a multicarrier system, only a small percentage of subcarriers will affected. We focus on the OFDM uplink and OFDMA downlink channel estimation based on IEEE 802.16e. Also, we use digital signal processor to implement OFDM uplink channel estimation schemes. The digital signal processing environment is Innovative Integration’s Quixote personal computer card, which hosts Texas Instruments’ TMS320C6416 which is a powerful signal processor with strong arithmetic operation capability. The channel estimation scheme can be separated into two stages. In the first stage, we use LS estimator for estimations of pilot subcarriers because of its low computational complexity. We study polynomial interpolations and cubic spline interpolations in frequency domain, NLMS adaptation algorithm, least squares in time domain, two-dimensional interpolations in time domain and maximum likelihood estimation. Finally, we did joint channel estimation and symbol detection to get better performance. Also we verify our simulation model on AWGN channel and then did the simulation on both static and time-variant fading channels. As for the DSP implementation, combination of linear interpolation and 2D interpolation are chosen due to computational complexity. In order to increase the efficiency, we also rewrite the original floating-point C program to fixed-point version and further refine our codes by taking into account the features of the DSP chip. In this thesis, we first introduce to standard of the IEEE 802.16e OFDM uplink and OFDMA downlink. Second, we describe the channel estimation techniques. Then the DSP implementation environment will be introduced. Finally, we discuss the channel estimation performance and the DSP implementation results.