發(fā)布時(shí)間：2018-06-17 18:18

  本文選題：SCMA + 碼本設(shè)計(jì)�。� 參考：《西南交通大學(xué)》2017年碩士論文

【摘要】：稀疏碼分多址(SCMA)技術(shù)是新一代5G通信技術(shù)的候選多址技術(shù)方案之一,該技術(shù)下,各個(gè)用戶的信號在資源上進(jìn)行非正交疊加,從而復(fù)用層數(shù)大于擴(kuò)頻因子,在資源數(shù)相同的情況下,系統(tǒng)能接入更多的用戶,使資源復(fù)用率大大提高。在LDS MA(Low Density Signature Multiple Access)的基礎(chǔ)上,SCMA將調(diào)制功能模塊和擴(kuò)頻功能模塊組合,將比特流直接映射成多維碼字。與LDS中固定使用QAM符號的策略相比,SCMA系統(tǒng)通過采用更加復(fù)雜精細(xì)的星座圖,來獲得更大的編碼與賦形增益,從而使得其系統(tǒng)性能優(yōu)于LDS。因此SCMA系統(tǒng)中的碼本設(shè)計(jì)是該研究方向的核心問題之一。研究表明,目前對SCMA碼本的研究多限于較低維度碼本,而對高維度的SCMA碼本的性能和檢測復(fù)雜度的討論較少。而事實(shí)上SCMA系統(tǒng)正是為接入海量用戶提供便利,因此研究高維度的SCMA碼本并分析其性能顯得很有意義。本論文研究了性能更優(yōu)的基于"Latin" rectangular的SCMA新型碼本構(gòu)造方法,構(gòu)造了高維度下的用戶碼本,并在高斯信道和瑞利衰落信道中對系統(tǒng)性能進(jìn)行了研究。高維度的碼本與優(yōu)化的MPA檢測算法進(jìn)行結(jié)合,在提高系統(tǒng)魯棒性的同時(shí)保證了較低的譯碼復(fù)雜度,因此擁有更優(yōu)異的系統(tǒng)綜合性能表現(xiàn)。在SCMA系統(tǒng)中,每個(gè)用戶都有一個(gè)特定的碼本,由碼本和映射矩陣編碼而成的碼字具有稀疏性,在解碼端采用具有良好性能的消息傳遞算法進(jìn)行檢測。傳統(tǒng)的ML算法需要進(jìn)行窮舉搜索,如此導(dǎo)致運(yùn)算復(fù)雜度很高,不利于實(shí)踐中推廣使用。因此SCMA系統(tǒng)借鑒了在LDPC碼中大量使用的MPA解碼算法,大大降低了多用戶系統(tǒng)的解碼復(fù)雜度。但是即便如此,在迭代次數(shù)過多,用戶數(shù)量大增,以及追求更大的系統(tǒng)分集增益的這些場景下,MPA算法復(fù)雜度也將急劇增加。因此本論文深入研究了解碼端的MPA算法。針對現(xiàn)有MPA算法復(fù)雜度較高的不足,對MPA算法進(jìn)行了優(yōu)化,研究了低譯碼復(fù)雜度的算法,并兼顧討論了算法對系統(tǒng)誤碼性能的影響。
[Abstract]:The sparse code division multiple access (SCMA) technology is one of the candidate multiple access schemes for the new generation 5G communication technology. Under this technology, the signals of each user are superposed on the resources, so that the number of multiplexed layers is greater than the spread spectrum factor. In the case of the same number of resources, the system can access more users, so that the reuse rate of resources is greatly improved. On the basis of low density signature multiple access, SCMA combines modulation function module with spread spectrum function module, and directly maps bit stream to multidimensional codeword. Compared with the strategy of using QAM symbols fixed in LDS, SCMA systems can obtain greater coding and shape gain by using more complex and fine constellation diagrams, thus making the system performance better than LDSs. Therefore, the codebook design in SCMA system is one of the core problems in the research direction. The research shows that most of the researches on SCMA codebook are limited to the lower dimension codebook, but the performance and detection complexity of the high dimensional SCMA codebook are less discussed. In fact, the SCMA system is convenient to access a large number of users, so it is meaningful to study the high-dimensional SCMA codebook and analyze its performance. In this paper, a novel codebook construction method based on "Latin" rectangular is studied, and the system performance in Gao Si channel and Rayleigh fading channel is studied in the Gao Si channel and Rayleigh fading channel. The combination of high-dimensional codebook and optimized MPA detection algorithm can improve the robustness of the system and ensure lower decoding complexity, so it has better performance. In the SCMA system, each user has a specific codebook. The codewords encoded by the codebook and the mapping matrix are sparse. At the decoding end, a message passing algorithm with good performance is used to detect the codewords. The traditional ML algorithm needs exhaustive search, which leads to high computational complexity, which is not conducive to popularization in practice. Therefore the SCMA system draws lessons from the MPA decoding algorithm which is widely used in LDPC codes and greatly reduces the decoding complexity of multi-user systems. But even if the number of iterations is too many, the number of users will increase greatly, and the complexity of the MPA algorithm will increase sharply in these scenarios where the system diversity gain is larger. Therefore, this paper deeply studies the MPA algorithm on the decoding side. In view of the high complexity of the existing MPA algorithm, the MPA algorithm is optimized, the algorithm with low decoding complexity is studied, and the influence of the algorithm on the system error performance is discussed.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN929.5

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前3條

1 肖琦;基于SCMA的D2D系統(tǒng)中無線資源管理研究[D];西南交通大學(xué);2016年

2 唐夢雪;SCMA系統(tǒng)低復(fù)雜度多用戶檢測算法研究[D];西南交通大學(xué);2016年

3 鮑鵬鑫;SCMA-OFDM系統(tǒng)中相位噪聲抑制算法研究[D];西南交通大學(xué);2016年

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本文編號：2031995