Non-orthogonal multiple access (NOMA) employed at the physical layer and network coding employed at the network layer are two promising transmission technologies to improve the spectral efficiency. In this paper, we develop a cross-layer approach by employing power-domain NOMA at the physical layer and instantly decodable network coding (IDNC) at the network layer in downlink broadcast communication systems. Following this approach, two IDNC packets are broadcasted during each transmission by employing superposition coding, one for all receivers and the other only for the strong receivers which employ successive interference cancellation (SIC). IDNC packets selection, transmission rates adaption, and NOMA power allocation are jointly considered to improve the throughput. Given the intractability of the problem, we decouple it into two separate subproblems, i.e., IDNC schedule and NOMA power allocation. IDNC schedule can be formulated as the maximum weight clique (MWC) problem, and two heuristic algorithms named as maximum weight vertex (MWV) search and maximum weight path based maximum weight vertex (MWP-MWV) search are developed to solve the first subproblem. An iterative function evaluation (IFE) approach is proposed to solve the second subproblem. Simulation results demonstrate the throughput gains of the proposed approach over the existing schemes.

Minimizing the decoding delay, the completion time, or the delivery time of instantly decodable network coding (IDNC) can all be approximated to a maximum weight clique (MWC) problem, which is well known to be NP hard. Due to its good tradeoff between performance and computational complexity, a heuristic approach named as maximum weight vertex (MWV) search is widely employed to select MWC for IDNC. However, in MWV, when there are few coding connection edges among the adjacent vertices of a vertex, its modified vertex weight cannot well reflect the weight of the MWC containing the vertex, which leads to incorrect selection of MWC. This paper proposes a new method to calculate the modified weight of a vertex by summing the weights of the vertices in the approximate maximum weight path (A-MWP) generated by this vertex. Since the vertices in an A-MWP can form a maximal clique, the proposed modified vertex weight may well indicate the weight of the MWC containing the vertex. The proposed algorithm has the same computational complexity as the MWV algorithm. Simulation results show that when employing any of the three performance metrics of IDNC, our proposed algorithm can achieve better system performance than the MWV algorithm.

In this paper, we study the decoding delay reduction problem for instantly decodable network coding (IDNC) with lossy feedback channels. In order to characterize the uncertainty of the reception state due to erasure feedback, we develop a statistical model of the state feedback matrix, whose elements are employed to indicate the likelihood of the reception status evaluated by the sender. The statistical model of the state feedback matrix can be updated according to the Markov model. With the established statistical model of the state feedback matrix, we build the statistical model of the IDNC graph, which can be used to indicate the likelihood of the coding opportunities among the vertices in the IDNC graph. The decoding delay reduction problem can be formulated as a maximum weight clique (MWC) problem. We develop two heuristic algorithms to solve the MWC problem, namely the maximum weight vertex (MWV) search and the approximate maximum weight path based MWV (A-MWP-MWV) search. Simulation results show that our proposed scheme based on statistical reception status model outperforms the scheme which keeps the reception state unchanged due to lossy feedback in estimating the reception status, and A-MWP-MWV outperforms MWV in solving the MWC problem without increasing additional complexity.

In B-IDNC (buffered instantly decodable network coding), each receiver can cache the non-instantly decodable network coded packets (NIDPs) which contain two wanted packets of the network layer for subsequent network decoding, so that more packets can be recovered at the network layer than the traditional instantly decodable network coding (IDNC). By employing B-IDNC, we consider a radio access network wherein a base station (BS) is required to broadcast a block of packets to a set of receivers. After completing network decoding at the network layer, each receiver can deliver its recovered packets from the network layer to the application layer in order. We consider minimizing the average packet access time of the application layer for B-IDNC. For the optimization problem is intractable, we approximate it to reduce the sum minimum access delay of the application layer across all receivers. The approximate problem is shown to be equivalent to a maximum weight encoding clique problem over the B-IDNC graph. We propose a simple heuristic algorithm based on greedy maximum weight vertex search to solve the approximate problem. Simulation results verify the effectiveness of our proposed algorithm as compared with the existing techniques.

The authors investigate the performance of the probabilistic data association (PDA) detector in a cooperative system that consists of a source, a relay and a destination, which are all multiantenna nodes. Taking advantage of the soft information provided by the PDA detector at the relay, the authors present a relaying scheme in light of which the relay can just transmit signals to the destination under the condition of having high detection reliability. Characterised by the means on how to exploit the information provided by both the source and the relay at the destination, two detectors named as combing PDA (C-PDA) and iterative PDA (I-PDA) are developed, respectively. C-PDA adopts one PDA detector to retrieve the transmit signals by combining the received signals from the source and the relay. I-PDA employs two concatenated PDA detectors to perform detection with respect to the received signals from the source and the relay, respectively. Just as in turbo decoding, soft information is iteratively exchanged between these two concatenated PDA detectors to enhance the performance of I-PDA. Simulation results have shown that significant performance gains can be achieved by both C-PDA and I-PDA over the conventional zero-forcing detector.