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The leitmotif of this paper aims at providing an architecture for the age of information (AoI) and cache-assisted hybrid multicast/unicast/device-to-device (D2D) transmission with the promising cell-free massive multiple-input multiple-output (MIMO) technology, for enriching data transmission rate, slackening the burden of high-volume data traffic, and boosting the system efficiency. Then, we design the user-centric transmission scheme and talk about the feasibility of the preliminary solutions for the multigroup multicast, D2D, wireless caching, and AoI, typically for signal processing, transmission mode selection mechanism, and cache replacement strategy. Finally, we also shall afford a viable research prediction containing an ensemble of the potential challenges and promising research directions to set the path for re-inventing an efficient sixth-generation (6G) communication system.

To fully utilize the scarce spectrum resources, the downlink device-to-device (D2D) underlaid multigroup multicast cell-free massive multi-input multi-output (MIMO) systems is proposed, where the geographically distributed access points (APs) serving both multi-antenna cell-free users (CFUEs) and D2D users (DUEs) pair over the same time/frequency resource blocks. Specially, the low-resolution analog-to-digital converters/digital-to-analog converters (ADCs/DACs) are adopted at the AP to effectively reduce hardware damage and energy costs. The imperfect channel state information (CSI) is obtained firstly by the standard minimum mean square error (MMSE), then the lower bounds of the closed-form achievable downlink rates for both CFUEs and DUEs are derived. Aside from that, the sum energy efficiency (EE) is also explored using the established power consumption model. Finally, numerical simulations are assessed to verify the analytical results and provide insights into the effects of the key system parameters. It demonstrates that increasing the number of APs can improve the sum SE, however, the sum EE decreases with the number of the APs sharply. Furthermore, increasing the density of DUEs can significantly improve the system capacity. The findings highlight the significance of the collaborative deployment of D2D and multigroup multicast cell-free massive MIMO technology, which can serve as a valuable reference and guide for the actual deployment of future communication systems.

Deploying long term evolution (LTE) system into unlicensed spectrum for offloading faces two challenges: 1) the metrics of instantaneous performance to characterize user satisfaction are no longer applicable due to non-contiguously available channel and 2) in a light traffic scenario, the channel utilization is low due to the added padding bits of simultaneously scheduled users. To tackle these two issues, dynamically configuring channel occupancy duration (COD) and flexibly allocating subcarriers are needed to design for the LTE system operating in unlicensed spectrum (LTE-U system). In this paper, the channel utilization in the COD and a unified user satisfaction are first defined to characterize the performance of LTE-U system. Then, a time-frequency two-dimention optimization problem is formulated to maximize the weighted sum of the two defined performance indexes. To achieve the tradeoff between the two performance indexes, a control factor is introduced. By using Lyapunov optimization and Dinkelback theory, an optimal time-frequency resource management algorithm is developed. The results show that the proposed algorithm outperforms the baselines, as the algorithm can flexibly balance the two performance indexes of the LTE-U system for diverse applications.

Machine-type communications are emerging as a new paradigm for enabling a broad range of applications from the massive deployment of sensor devices to mission-critical services. To support massive machine-to-machine (M2M) communications with delay constraints in cellular networks, we design an efficient random access and data transmission system known as distributed queueing random access-multiple-input multiple-output (DQRA-MIMO) data transmission system. This system has the advantages of both efficient collision resolution of DQRA protocol and the efficient data transmission of MIMO technology. To obtain higher throughput under delay constraint and limited time-frequency resources, we match the ability of collision resolution with the capability of MIMO transmission by optimally configuring system parameters. The closed-form expression of throughput is derived, which is a function of the total user equipments' traffic arrival rate, average packet number of each arrival, number of base station antennas, and number of access request (AR) slots. An optimization problem is formulated to maximize the throughput to obtain the optimal number of AR slots given a certain delay constraint for M2M traffic. Numerical and simulation results reveal that, for a given requirement of average delay, the proposed optimized DQRA-MIMO system, which dynamically adjusts time-frequency resource division to maximize throughput, can provide a higher throughput than that of a baseline approach.