針對某些使用極化碼的通訊系統的通道估測

Abstract

極化碼是一種由 E. Arikan 於 2009 年提出的新型錯誤更正碼。它利用通道極化的現象，透過精心設計的編碼和解碼方式，使某些通道的容量接近 1，而其他通道的容量則趨於 0。極化碼已被證明可以在任何二元離散無記憶通道中達到香農極限。 本文首先回顧了極化碼的基礎知識，包括通道合併和編碼方式。隨後，我們對極化碼的性能進行了分析和比較，包括 SC 解碼、SCL 解碼和 CA-SCL 解碼。 針對通道狀態資訊 (CSI) 未知的衰落通道，本文研究了極化編碼系統的通道估計問題。我們採用了導頻輔助塊傳輸系統 (PAT) 和分群演算法進行盲通道估計。此外，我們還利用微分編碼 (DE) 和非同調塊編碼 (NBC) 來解決在二進制相位偏移調制 (BPSK) 和四進制相位偏移調制 (QPSK) 場景下出現的相位模糊問題。最後，我們將通道狀態資訊 (CSI) 未知的衰落通道場景擴展到了 GDMA 系統和 OFDM 系統，對不同的通道估計方法進行了比較，分析了它們的優劣。

Polar codes, introduced by E. Arikan in 2009, form a novel type of error correction code. They leverage the phenomenon of channel polarization, employing carefully designed coding and decoding schemes to achieve near-capacity performance for some channels while driving the capacity of others to zero. Polar codes have been proven to achieve the Shannon limit for any binary discrete memoryless channel. This paper begins by reviewing the fundamental concepts, including channel combining and encoding techniques. Subsequently, we analyze and compare the performance of different decoding algorithms for polar codes: SC decoding, SCL decoding, and CA-SCL decoding. Focusing on fading channels with unknown channel state information (CSI), this paper investigates the channel estimation problem in polar-coded systems. We employ pilot-assisted block transmission (PAT) and clustering algorithms for blind channel estimation. Additionally, we utilize differential encoding (DE) and noncoherent block coding (NBC) to address phase ambiguity issues encountered in binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) scenarios. Finally, we extend the scenario of fading channels with unknown CSI to GDMA systems and OFDM systems, comparing different channel estimation methods and analyzing their performance advantages and disadvantages.