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We propose a joint channel estimation and signal detection approach for the uplink non-orthogonal multiple access (NOMA) using unsupervised machine learning. We apply a Gaussian mixture model (GMM) to cluster the received signals, and accordingly optimize the decision regions to enhance the symbol error rate (SER) performance. We show that, when the received powers of the users are sufficiently different, the proposed clustering-based approach achieves an SER performance on a par with that of the conventional maximum-likelihood detector (MLD) with full channel state information (CSI). We study the tradeoff between the accuracy of the proposed approach and the blocklength, as the accuracy of the utilized clustering algorithm depends on the number of symbols available at the receiver. We provide a comprehensive performance analysis of the proposed approach and derive a theoretical bound on its SER performance. Our simulation results corroborate the effectiveness of the proposed approach and verify that the calculated theoretical bound can predict the SER performance of the proposed approach well. We further explore the application of the proposed approach to a practical grant-free NOMA scenario, and show that its performance is very close to that of the optimal MLD with full CSI, which usually requires long pilot sequences.

Short analog fountain code (AFC) is a promising channel code for short packet communications, particularly in ultra-reliable and low latency communications (URLLC) scenarios. This letter proposes a short partitioned transmission strategy based on AFC (PT-AFC) to further enhance the error rate and latency performance of AFC at short block lengths. The key idea is to partition the information block into multiple short blocks, each being encoded using an AFC, and then concatenate the AFC coded symbols. The partitioning of the message allows for parallel decoding of various partitions at the receiver, which significantly reduces the overall latency. Additionally, this letter provides an analytical framework to minimize the number of short cycles in the bipartite graph of the respective code, where we determine an upper bound on the number of partitions, given the information block length and code rate. Simulation results show that PT-AFC outperforms existing AFC schemes with significantly reduced latency.

The rateless multiple access (RMA) scheme is a promising distributed multiple access scheme to achieve simultaneous high reliability, low latency and massive connectivity. In this paper, we investigate the maximum likelihood (ML) decoding performance of the RMA scheme in an Additive white Gaussian noise (AWGN) channel with binary phase-shift keying (BPSK) modulation. For the first time, this paper derives the ensemble weight distribution of the RMA scheme. We derive an upper bound on the decoding error performance of the RMA scheme under ML decoding in an AWGN channel with BPSK modulation. Using the derived bound as the fitness function, we adopt the continuous genetic algorithm to optimize the parameters of the RMA scheme. Simulation results show the tightness of the derived bound and the superiority of the optimized degree distribution over the conventional degree distributions.

In this letter, we propose a dynamic re-transmission strategy for the two-user uplink non-orthogonal multiple access scenario (NOMA) with hybrid automatic repeat request (HARQ) and more than one allowed re-transmissions. In the proposed scheme, whenever both users simultaneously receive negative acknowledgment (NACK) from the base station (BS), the high-power user is asked to re-transmit its previous packet, while the low-power user is requested to send a new packet in the next time slot. The low-power user is allowed to retransmit its previous packets when the other user stops the re-transmission. We propose a Markov model to analyze the dynamics of the proposed scheme and the conventional scheme, where the users always send the re-transmission when receiving a NACK from the BS. We find the optimal power splitting ratios to minimize the maximum packet error rate (PER) amongst users. Simulation results show that the proposed dynamic approach significantly improves the PER of the low-power user at the expense of a negligible increase in the PER of the high-power user.

This article reviews the potential channel decoding techniques for ultra-reliable low-latency communications (URLLC). URLLC is renowned for its stringent requirements including ultra-reliability, low end-to-end transmission latency, and packet-size flexibility. These requirements exacerbate the difficulty of the physical-layer design, particularly for the channel coding and decoding schemes. To satisfy the requirements of URLLC, decoders must exhibit superior error-rate performance and low decoding complexity. Also, it is desired that decoders be universal to accommo-date various coding schemes. This article provides a comprehensive review and comparison of different candidate decoding techniques for URLLC in terms of their error-rate performance and computational complexity for structured and random short codes. We further make recommendations of the decoder selections and suggest several potential research directions.

In this paper, we develop a density evolution (DE) framework for analyzing the iterative joint decoding (JD) for non-orthogonal multiple access (NOMA) systems, where the ordered-statistics decoding (OSD) is applied to decode short block codes. We first investigate the density-transform feature of the soft-output OSD (SOSD), by deriving the density of the extrinsic log-likelihood ratio (LLR) with known densities of the priori LLR. Then, we represent the OSD-based JD by bipartite graphs (BGs), and develop the DE framework by characterizing the density-transform features of nodes over the BG under the binary phase shift keying (BPSK) transmission. Numerical examples show that the proposed DE framework accurately tracks the evolution of LLRs during the iterative decoding, especially at moderate-to-high SNRs. Based on the DE framework, we further analyze the BER performance of the OSD-based JD, and the convergence points of the two-user and equal-power systems.

Single-carrier frequency-division multiple access (SC-FDMA) based index modulation (IM), referred here as SC-IM, allows users to implicitly transmit a part of their data bits by switching on some of their allocated subcarriers, followed by ${M}$ -ary constellation symbols transmission over the activated subcarriers. This sparse use of subcarriers provides better energy efficiency and error rate. Using these benefits, this letter exploits SC-IM with uplink power domain non-orthogonal multiple access (NOMA), where all users with the same allocated subcarrier set can simultaneously transmit their SC-IM data with different power levels, which are exploited by the receiver to perform multi-user detection. Performance of the proposed technique is analyzed and compared with conventional NOMA. It is shown that the proposed scheme can achieve energy efficient massive connectivity, which is a primary requirement for massive machine-type communications.

In this letter, we represent Raptor codes using a multi-edge framework, which gives a general framework to design them for higher-order modulation using multi-edge type density evolution. We then propose an efficient Raptor code design method for higher-order modulation, where we design distinct degree distributions for distinct bit levels. We consider a joint decoding scheme based on belief propagation for Raptor codes and also derive an exact expression for the stability condition. In several examples, we demonstrate that the higher-order modulated Raptor codes designed using the multi-edge framework outperform previously reported higher-order modulation codes in literature.

Grant‐free access has been identified as a potential solution to support massive machine‐type communications by avoiding the high signaling overhead and latency issues of existing grant‐based channel access mechanisms. Motivated by this, the work in this article proposes a simple, yet efficient, strategy to enable power domain non‐orthogonal multiple access (PD‐NOMA) aided grant‐free communication, where devices can transmit their data in an arrive‐and‐go manner by using randomly chosen power levels. The focus here is on collision detection, which is of prime importance in grant‐free systems. In the considered grant‐free PD‐NOMA scheme, collisions occur when multiple users randomly choose the same resource block and power level for data transmission, which makes it difficult for the base station (BS) to distinguish between their data. Accordingly, the proposed technique aims at early collision detection by introducing special activity indicator symbols (AIS), which are transmitted by each active device before, or at the start of, the actual data packet. The BS then exploits these known AIS to identify successful transmissions and collisions before processing actual data, which avoids unnecessary data transmission by users and/or receiver processing in case of collisions, and prepares the receiver for appropriate data recovery otherwise. It is demonstrated that the proposed technique provides a low complexity and high performance solution to enable transmission status detection in grant‐free PD‐NOMA. This article proposes an efficient method to detect transmission status in grant‐free non‐orthogonal multiple access, which is identified as a potential technology to support the massive Internet of Things communication. The simulation results, along with detailed mathematical analysis, demonstrate that the proposed method achieves high performance gains while having a low computational complexity. Large number of users in the system; a lower number of users (colored) become active at a time slot.Active users transmit their data by choosing a receive power level from the predefined levels.If multiple active users choose the same power, a collision takes place, for example, in time slot 2.BS needs to detect the transmission status, that is, successful transmissions and collisions.

Cognitive radio (CR) heterogeneous network (HetNet) is an emerging technology that aims at enhancing spectrum utilization through spectrum sharing among macro base stations and femto base stations. Similar to other CR networks, in CR HetNets, providing the desired quality of service for the licensed primary users (PUs) is of utmost importance. Due to the shared spectrum between PUs and cognitive secondary users (CSUs) as well as offloading policies, the spectrum handover (SHO) process must be carefully designed. Using the idea of reserved channels, this paper proposes 2 traffic‐aware SHO schemes for cognitive HetNets. In the proposed schemes, each CSU can adopt either a shared‐to‐reserved or a reserved‐to‐shared SHO strategy. The proposed approaches can be implemented in both distributed and centralized manners to maintain a trade‐off between performance and complexity. The performance of the proposed schemes is mathematically analyzed, and closed‐form expressions are derived for the blocking probability of the PUs and the forced termination probability of the CSUs. Numerical results show that the proposed schemes outperform the existing SHO approaches, such as always‐change, always‐stay, and proactive methods, specifically at higher arrival rates of PUs. Moreover, several evaluation metrics, such as effective throughput, energy efficiency, and a proposed combinational utility function, are investigated for both distributed and centralized schemes. The results show that the proposed centralized schemes offer higher performance compared to the distributed schemes. This paper proposes two traffic‐aware spectrum handover (SHO) schemes for cognitive HetNets, which use shared‐to‐reserved (SR) or reserved‐to‐shared (RS) SHO strategies. The performance of the proposed schemes is mathematically analyzed and two closed‐form expressions are derived for blocking probability of the primary users and forced termination probability of the cognitive secondary users. Numerical results show that the proposed schemes outperform the existing SHO approaches, such as always‐change, always‐stay, and proactive methods, specifically at higher arrival rates of primary users and also the proposed centralized schemes offer higher performance compared to the distributed ones.

With the rise of cheap small cells in wireless cellular networks, there are new opportunities for third party providers to service local regions via sharing arrangements with traditional operators. In fact, such arrangements may be particularly desirable for large facilities—such as stadiums, universities, and mines—as they already need to cover property costs, and often have fiber backhaul and efficient power infrastructure. In this paper, we propose a network-sharing arrangement between large facilities and traditional operators. Our network-sharing arrangement consists of two aspects: leasing of data access and spectrum from traditional operators; and service agreements with users. As a consequence of the incorporation of the user service agreements into the sharing arrangement, financial as well as physical resource constraints need to be accounted for. This introduces a new dimension into wireless network resource allocation, which requires a new evaluation framework. To this end, we develop a framework based on ruin theory, where the key metric is the probability that the facility is insolvent within a fixed time period. We then investigate the effect of initial capital and physical layer parameters on the ruin probability, which provides insight into the robustness of the network-sharing arrangement to varying conditions. There are now new opportunities for third party providers to service local regions via sharing arrangements with traditional operators. In this paper, we propose a network sharing arrangement with facilities. This motivates an evaluation framework beyond the expected profit, which we explore using techniques from ruin theory.