To support the newly introduced multimedia services with ultra-low latency and extensive computation requirements, resource-constrained end-user devices should utilize the ubiquitous computing resources available at network edge for augmenting on-board (local) processing with edge computing. In this regard, the capability of cell-free massive MIMO to provide reliable access links by guaranteeing uniform quality of service without cell edge can be exploited for a seamless parallel computing. Taking this into account, we formulate a joint communication and computing resource allocation (JCCRA) problem for a cell-free massive MIMO-enabled mobile edge computing (MEC) network with the objective of minimizing the total energy consumption of the users while meeting the ultra-low delay constraints. To derive efficient and adaptive JCCRA scheme robust to network dynamics, we present a distributed solution approach based on cooperative multi-agent reinforcement learning. The simulation results demonstrate that the proposed distributed approach can achieve comparable performance to a centralized deep deterministic policy gradient (DDPG)-based target benchmark, without incurring additional overhead and time cost. It is also shown that our approach significantly outperforms heuristic baselines in terms of energy efficiency, roughly up to 5 times less total energy consumption. Furthermore, we demonstrate substantial performance improvement compared to cellular MEC systems.

Modeling the base station deployments with stochastic geometry in the cellular network, we derive the coverage probability and average rate of typical user under a generalized composite fading channel, which is composed of the shadowing and Nakagami-m fading. Unlike the previous work, the current coverage analysis does not involve any numerical integration, allowing for a rather straightforward evaluation of the required signal-to-interference ratio with the given target cellular performance under general channel environments. It approximates a gamma-lognormal distribution, which characterizes an effect of composite fading, as a weighted sum of gamma distributions by the Gaussian-Hermite quadrature for analytical tractability.

For the frequency division duplexing-based large-scale multiple-input multiple-output (MIMO) systems, we consider a multi-user MIMO (MU-MIMO) non-orthogonal multiple access (NOMA) scheme, referred to as beam division-NOMA (BD-NOMA), which is featured by a long-term feedback-based user grouping and clustering, along with a short-term feedback-based BD-NOMA scheduling. The performance of BD-NOMA is not warranted in practice because near users are severely interfered by strong signals for the far users of other beams, and furthermore, the long-term feedback-based user grouping and clustering might result in short-term inter-beam interference. We consider the short-term feedback-based joint optimization problem of user selection and power allocation for NOMA in each beam and system-wide power allocation for MU-MIMO, dealing with both intra-beam and inter-beam interference at the same time. We formulate a joint optimization problem for a large-scale MIMO system with the multiple channel quality indicators-based short-term feedback. In our analysis, we reformulate the original problem into an equivalent one that can be solved iteratively with the weighted minimum mean square error-based algorithm. Then, the performance analysis is presented to conclude that the proposed optimization is essential for enabling BD-NOMA to outperform beam division multiple access, especially when inter-beam interference becomes critical.

In sparse code multiple access (SCMA)-based grant-free (GF) access, both user’s channel and the selected SCMA codebook (CB) are considered as a transmission signature for multi-user detection (MUD). In conventional SCMA-based grant-free (GF) access where a single codebook (CB) is employed per a user’s random access transmission, however, random selection of CBs and random fading channel reduce the minimum Euclidean distance among overloaded layers (signatures). This significantly degrades the performance. Furthermore, it is also challenging to reduce the collision rate in the course of selecting random access resources while maintaining low preamble overhead. In this paper, we consider a new approach that maps user’s consecutive symbols to codewords from the different SCMA CBs in a round-robin manner. It is shown that a combinatorial nature of multiple CBs and the inherent code diversity therein allow to simultaneously reduce collision probability while providing sufficient separation among transmissions, consequently decreasing users’ activity misdetection rate. It is also shown that the proposed multi-codebook SCMA (MC-SCMA)-based GF access scheme outperforms the conventional single CB-based SCMA version by overloading of more users (almost up to 200%) as it allows a large number of highly non-orthogonal preambles to be employed while keeping the same preamble length (overhead). Finally, we conclude that the proposed joint design of non-orthogonal preambles and data transmission based on multiple CBs provides a significant performance improvement for the grant-free access system. It can also readily be extended to other code-based non-orthogonal multiple access (NOMA) schemes.

Grant-free (GF) access has been one of the enablers for the various use cases in 5th generation (5G) mobile system, especially for time-critical massive machine-type communication (mMTC). However, these use cases have diverse quality of service (QoS) requirements, which can be measured in terms of an access success rate from a GF random access perspective. Consequently, a GF scheme that enables supporting of diverse QoS is highly sought. This paper proposes a GF access scheme in which high-QoS users superpose multiple preambles to improve their access success rate as a result of the diversity in access collision and multiple access interference seen by multiple preambles. We further show that in the presence of multiple antennas in the base station (BS), a low-complexity receiver can correctly detect active preambles with a significantly high probability, even under severe multiple access interference caused by non-orthogonal preamble transmission. An theoretical performance analysis is conducted by modeling the preamble reception as a multiple measurement vector-based compressive sensing problem. The preamble misdetection probability is shown to decrease exponentially as the number antennas at BS increases. Numerical results demonstrate multiple-order improvement in terms of the access success rate for critical-QoS users, even under severe noise and multiple access contamination.