Non-orthogonal multiple access (NOMA) is a promising candidate radio access technology for future wireless communication systems, which can achieve improved connectivity and spectral efficiency. Without sacrificing error rate performance, link adaptation combining with adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) can provide better spectral efficiency and reliable data transmission by allowing both power and rate to adapt to channel fading and enabling re-transmissions. However, current AMC or HARQ schemes may not be preferable for NOMA systems due to the imperfect channel estimation and error propagation during successive interference cancellation (SIC). To address this problem, a reinforcement learning based link adaptation scheme for downlink NOMA systems is introduced in this paper. Specifically, we first analyze the throughput and spectrum efficiency of NOMA system with AMC combined with HARQ. Then, taking into account the imperfections of channel estimation and error propagation in SIC, we propose SINR and SNR based corrections to correct the modulation and coding scheme selection. Finally, reinforcement learning (RL) is developed to optimize the SNR and SINR correction process. Comparing with a conventional fixed look-up table based scheme, the proposed solutions achieve superior performance in terms of spectral efficiency and packet error performance.

In this paper, we investigate the throughput performance of single-packet and multi-packet hybrid-automatic repeat request (HARQ) with blanking for downlink non-orthogonal multiple access (NOMA) systems. While conventional single-packet HARQ achieves high throughput at the expense of high latency, multi-packet HARQ, where several data packets are sent in the same channel block, can achieve high throughput with low latency. Previous works have shown that multi-packet HARQ outperforms single-packet HARQ in orthogonal multiple access (OMA) systems, especially in the moderate to high signal-to-noise ratio regime. This work amalgamates multi-packet HARQ with NOMA to achieve higher throughput than the conventional single-packet HARQ and OMA, which has been adopted in the legacy mobile networks. We conduct theoretical analysis for the throughput per user and also investigate the optimization of the power and rate allocations of the packets, in order to maximize the weighted-sum throughput. It is demonstrated that the gain of multi-packet HARQ over the single-packet HARQ in NOMA systems is reduced compared to that obtained in OMA systems due to inter-user interference. It is also shown that NOMA-HARQ cannot achieve any throughput gain with respect to OMA-HARQ when the error propagation rate of the NOMA detector is above a certain threshold.

This paper considers the problem of source coding with side information at the decoder, also called Slepian-Wolf source coding scheme. In practical applications of this coding scheme, the statistical relation between the source and the side information can vary from one data transmission to another, and there is a need to adapt the coding rate depending on the current statistical relation. In this paper, we propose a novel rate-adaptive code construction based on LDPC codes for the Slepian-Wolf source coding scheme. The proposed code design method allows to optimize the code degree distributions at all the considered rates, while minimizing the amount of short cycles in the parity check matrices at all rates. Simulation results show that the proposed method greatly reduces the source coding rate compared to the standard low density parity check accumulated (LDPCA) solution.

In this paper, we consider the construction of a Slepian-Wolf source coding scheme in a context where only a small amount of data has to be transmitted to the decoder. In this context, we propose a novel rate-adaptive Slepian-Wolf code construction that is based on non-binary LDPC codes. The construction we propose replaces the regular accumulator of the standard LDPCA method by a local graph that is optimized at every rate of interest. In our method, the local graph is specifically designed in order to give good decoding performance at short length, while existing LDPCA constructions are usually optimized under an infinite codeword length assumption. Our simulation results on short codes obtained from our design method show a FER improvement of up to an order to magnitude compared to the standard LDPCA construction.

This paper studies secure communication based on incremental redundancy (INR) secure hybrid automatic retransmission request (HARQ) protocol over block-fading wiretap channels. The transmitter has no instantaneous channel state information (CSI) available from either main channel or the eavesdropper channel, hence the coding rates cannot be adapted to instantaneous channel conditions. We investigate the outage performance for two schemes of INR secure HARQ protocols: case 1) when there exists two reliable multibit feedback channels from both legitimate receiver and eavesdropper to the transmitter carrying a function of outdated CSI, and case 2) when there is a multibit feedback channel only from legitimate receiver. In both cases, we demonstrate that using the information carried via multibit feedback channels, the transmitter can adapt the coding rates in order to achieve a better secrecy throughput using a smaller number of transmissions comparing to the ACK/NACK feedback channel model. For some parameters, our rate adaptation protocol achieves a strictly positive secrecy throughput whereas it is equal to zero for the protocol with ACK/NACK feedback. We show that for some set of parameters, the loss of secrecy throughput between case 1 and case 2 is very small compared to the gain provided by both protocols.

This paper considers the Broadcast Channel with Confidential Message (BCCM) where the sender attempts to send altogether a common message to two receivers and a confidential message to one of them. The achievable rate regions are derived for the power-constrained Gaussian BCCM with finite input alphabet using various transmission strategies. Namely, time sharing, superposition modulation and superposition coding are used as broadcast strategies. For superposition modulation and superposition coding, the maximal achievable rate regions are obtained by maximizing over both constellation symbol positions and the joint probability distribution. The maximization of the secrecy rate for wiretap channels is also studied as a particular case of the BCCM problem. We compare the considered transmission strategies in terms of percentage gains in achievable rates. We concentrate on the impact of the finite alphabet constraint on achievable rates, and show that this constraint may change well known results obtained in the Gaussian case. We show also that the secrecy constraint can change the shape of the achievable rate region in superposition modulation used in some standards when symbols are equiprobable. On a more practical side, it is shown that a performance close to the optimum can be obtained by strategies with reduced complexity.

This paper investigates the maximization of the secrecy-achievable rate region for the Gaussian broadcast channel with confidential message (BCCM) using finite input constellations. The maximization is done jointly over symbol positions and their joint probabilities. The secrecy-achievable rate regions are given for various broadcast strategies which differ in their complexity of implementation. We compare these strategies in terms of improvement in achievable rates and we study the impact of finite input alphabet on the secrecy-achievable rates. It is shown that finite alphabet constraints may change well known results holding in the Gaussian case.