Massive machine-type communications (mMTC) is one of the main three focus areas in the 5th generation (5G) of wireless communications technologies to enable connectivity of a massive number of internet of things (IoT) devices with little or no human intervention. In conventional human-type communications (HTC), due to the limited number of available channel resources and orthogonal resource allocation techniques, users get a transmission slot by making scheduling/connection requests. The involved control channel signaling, negligible with respect to the huge transmit data, is not a major issue. However, this may turn into a potential performance bottleneck in mMTC, where huge number of devices transmit short packet data in a sporadic way. To tackle the limited radio resources and massive connectivity challenges, non-orthogonal multiple access (NOMA) has emerged as a promising technology that allows multiple users to simultaneously transmit their data over the same channel resource. This is achieved by employing user-specific signature sequences at the transmitting devices, which are exploited by the receiver for multi-user data detection. Due to its massive connectivity potential, NOMA has also been considered to enable grant-free transmissions especially in mMTC, where devices can transmit their data whenever they need without the scheduling requests. The existing surveys majorly discuss different NOMA schemes, and exploit their potential, in typical grant-based HTC scenarios, where users are connected with the base station, and various system parameters are pre-defined in the scheduling phase. Different from these works, this survey provides a comprehensive review of the recent advances in NOMA from a grant-free connectivity perspective. Various grant-free NOMA schemes are presented, their potential and related practical challenges are highlighted, and possible future directions are thoroughly discussed at the end.

Millimeter wave (mmWave) has been claimed to be the only viable solution for high-bandwidth vehicular communications. However, frequent channel estimation and beamforming required to provide a satisfactory quality of service limits mmWave for vehicular communications. In this paper, we propose a novel channel estimation and beam tracking framework for mmWave communications in a vehicular network setting. For channel estimation, we propose an algorithm termed robust adaptive multi-feedback (RAF) that achieves comparable estimation performance as existing channel estimation algorithms, with a significantly smaller number of feedback bits. We derive upper and lower bounds on the probability of estimation error (PEE) of the RAF algorithm, given a number of channel estimations, whose accuracy is verified through Monte Carlo simulations. For beam tracking, we propose a new practical model for mmWave vehicular communications. In contrast to the prior works, the model is based on position, velocity, and channel coefficient, which allows a significant improvement of the tracking performance. Focused on the new beam tracking model, we re-derive the equations for Jacobian matrices, reducing the complexity for vehicular communications. An extensive number of simulations is conducted to show the superiority of our proposed channel estimation method and beam tracking algorithm in comparison with the existing algorithms and models. Our simulations suggest that the RAF algorithm can achieve the desired PEE, while on average, reducing the feedback overhead by 75.5% and the total channel estimation time by 14%. The beam tracking algorithm is also shown to significantly improve beam tracking performance, allowing more room for data transmission.

We propose a novel random access (RA) scheme with the quality of service (QoS) guarantees for machine-to-machine (M2M) communications. We consider a slotted uncoordinated data transmission period during which machine type communication (MTC) devices transmit over the same radio channel. Based on the latency requirements, MTC devices are divided into groups of different sizes, and the transmission frame is divided into sub-frames of different lengths. In each sub-frame, each group is assigned an access probability based on which an MTC device decides to transmit replicas of its packet or remain silent. The base station employs successive interference cancellation to recover all the superposed packets. We derive the closed-form expressions for the average probability of device resolution for each group, and we use these expressions to design the access probabilities. The accuracy of the expressions is validated through Monte Carlo simulations. We show that the designed access probabilities can guarantee the QoS requirements with high reliability and high energy efficiency. Finally, we show that RA can outperform standard coordinated access schemes as well as some of the recently proposed M2M access schemes for cellular networks.

Adaptive coding and modulation in current cellular networks relies on a channel quality indicator fed back from the receiver to the transmitter. The process of acquiring channel state information at the transmitter (CSIT) is estimated to take 5-8 ms. For short-packet transmissions in machine-type communications (MTC), the data transmission of small payloads is estimated to take a fraction of a millisecond, i.e., a fraction of the end to end latency. This is especially problematic for ultra-reliable low-latency communications (URLLC) that require an end-to-end latency of 1 ms only. To this end, self-adaptive coding and modulation, aka rateless coding, is much needed to cater for these stringent requirements. In this letter, a new design is proposed for the recently proposed class of rateless codes, dubbed analog fountain codes (AFC), tailored for short-packet transmissions. The numerical results show no error floors down to block error rates of 10 ^-7 , thus meeting the ultra-high reliability requirement of URLLC.

In this paper, we focus on the design and analysis of the Analog Fountain Code (AFC) for short packet communications. We first propose a density evolution (DE) based framework, which tracks the evolution of the probability density function of the messages exchanged between variable and check nodes of AFC in the belief propagation decoder. Using the proposed DE framework, we formulate an optimisation problem to find the optimal AFC code parameters, including the weight-set, which minimises the bit error rate at a given signal-to-noise ratio (SNR). Our results show the superiority of our AFC code design compared to existing designs of AFC in the literature and thus the validity of the proposed DE framework in the asymptotically long block length regime. We then focus on selecting the precoder to improve the performance of AFC at short block lengths. Simulation results show that lower precode rates obtain better realised rates over a wide SNR range for short information block lengths. We also discuss the complexity of the AFC decoder and propose a threshold-based decoder to reduce the complexity.