IEEE 802.16m 之初始下行同步

Abstract

當一個行動電話開始要進入網路的時候，我們必須與基地台做初始的同步。在初始的同步中，包含了符元時間偏移、載波偏移和前置符元序號(preamble index)需要同步估測。我們利用前置符元的功率較一般資料符元(data symbol)大的特性做功率移動累加，藉由找到累加結果的峰值來估測前置符元的起始位置。由此起始位置向後推算一個符元長度以當作我們所估測出來的前置符元，而與真實的前置符元存在一個相位性錯誤(phase error)。我們利用此估測出來的前置符元推導其近似最大可能性估測(quasi maximum likelihood)以求得小數部分載波偏移和導出前置符元的通道估測的式子。我們在頻域上將此通道估測的式子經由估測出來的小數部分載波偏移補償之後，代入由合理範圍的整數部分載波偏移和不同的前置符元而得到的通道脈衝響應。再計算這些通道脈衝響應不同的精準符碼時間偏移序號64點功率和並且選出最大的那一個，其所在的整數部分載波偏移、前置符元和精準符碼時間偏移序號即為此聯合估測的結果。 本篇論文介紹IEEE 802.16m系統裡關於下行初始同步的問題、演算法推導、以及程式模擬方面的議題。首先簡介IEEE 802.16m下行的標準機制及相關架構，接著提出同步問題並提供演算法的設計發想及推導，而後將整個演算法的流程用浮點數運算來驗證，設計出一個合理的IEEE 802.16m接收訊號模型，在可加性白色高斯雜訊(additive white Gaussian noise, AWGN)通道之下得到的數據來驗證演算法的特性，然後在多路徑衰減(multipath fading)通道傳輸中使用數種不同多路徑通道、相對移動車速以及訊雜比(signal to noise ratio, SNR)來測試演算法對多路徑效應、通道衰減以及相對速度引起的都普勒頻移(Doppler shifts)所產生的影響。

This thesis introduces some topics about initial downlink synchronization, algorithm derivations, and program simulations of IEEE 802.16m system. When a mobile station entering to the network, it needs to perform initial synchronization, including of symbol timing offset, carrier frequency offset and preamble index. We utilize the trait which the power of preamble is larger than it of the common data symbol to compute the moving power sum, and then estimate the left boundary of preamble by finding out the peak value of moving power sum. A symbol period from this estimated boundary is regarded as the estimated preamble, which has a phase noise with the exact preamble. We derive the quasi maximum likelihood estimation from the likelihood function of the estimated preamble to obtain fractional carrier frequency offset (FCFO) and the formula of channel estimation. After compensating the estimated fractional carrier frequency offset to the formula of channel estimation, we substitute several reasonable integral carrier frequency offsets (ICFOs) and primary advanced preambles (PA-Preambles) into this formula and obtain channel impulse responses (CIRs). After that, we compute different fine timing offset index 64-points power sum of these CIRs and find out the peak value whose ICFO, PA-Preamble index, and fine timing offset index are regarded as the result of the joint estimation. In terms of simulations, above all, we present a reasonable received signal model of IEEE 802.16m, and then simulate our algorithm in floating point under AWGN (additive white Gaussian noise) channel to verify its performance. Moreover, we test this algorithm under different multipath fading channels, Pedestrian B and SUI-5, at different speed which cause Doppler shifts, and signal to noise ratio (SNR) to observe the effect on this algorithm.