Joint Constellation and Code Design for the Gaussian Multiple Access Channel
|關鍵字:||低密度奇偶檢查碼;多重存取通道;高斯逼近;外部信息圖;二元星座點;LDPC codes;Multiple Access Channel;Gaussian Approximation;EXIT Charts;Binary Constellation|
頻多工存取，2G 的分時多工存取，3G 的分碼多工存取到4G 的正交分頻多工存取，而
Multiple access techniques are at the core of the evolution in wireless communications technologies. Frequency-division multiple access (FDMA) was first employed used for 1G, time-division multiple access (TDMA) for 2G, 3G relies on code-division multiple access (CDMA), and orthogonal frequency-division multiple access (OFDMA) is employed in 4G. The above techniques all rely on the orthogonalization of the users’ transmissions toward the base station. However, due to the rapid development of wireless communication, orthogonalization of the transmissions is no longer sufficient to support the demand of the various wireless devices. To satisfy these requirements, non-orthogonal multiple access (NOMA) has been proposed in 5G. NOMA allows multiple users to share time and frequency simultaneously in a certain location: the information theoretical channel model which addresses the simultaneous transmission of information of two encoders toward a central unit is the multiple access (MAC) channel. Unfortunately, although this model is very well understood from an information theoretic perspective, practical coding and modulation schemes which are practically relevant are yet to be developed. In this thesis, we consider the joint design of both transmit constellation and LDPC codes for the two users, symbol-synchronous, binary-input Gaussian multiple access channel. We consider the problem of attaining the symmetric capacity without the use of time-sharing or rate-splitting by joint decoding of the noisy sum of two LDPC codewords. To this end, a decoding algorithm is considered which extends the classic belief propagation algorithm to allow for the simultaneous decoding of two codewords. We then exploit a Gaussian approximation of the message distribution and EXIT charts to investigate the convergence of the decoding process and also introduce a linear programming technique for joint code design. For this decoding algorithm and proposed code optimization procedure, different constellation choices are obtained which perform well in different SNR regimes. In particular, it is shown that, quite surprisingly, in the moderate SNR regime the best performance is obtained by an asymmetric constellation.