Achieving energy-efficient massive ultrareliable and low-latency communications (E2-mURLLC) is a promising application prospect for sixth-generation (6G) mobile communication networks. However, there are some insurmountable obstacles, such as a large number of potential users, complex and diverse small-scale and shadow fading, and stringent energy efficiency (EE), reliability, and latency requirements. Considering the above obstacles, we propose a cell-free massive multiple-input–multiple-output (MIMO) architecture based on the $\kappa $ - $\mu $ shadowed fading model, and maximum-ratio combining (MRC) multiuser detection with simple path-loss decoding (S-PLD) to achieve the simultaneous optimization of EE, latency, and reliability. Furthermore, the finite blocklength information theory is used to uncover the relationship among EE, reliability, latency, and achievable data rate when the packet size is small. Simulation results show that compared with the massive MIMO architecture, using our architecture with MRC multiuser detection and S-PLD can support a threefold increase in the number of access users, reduce transmit power by 90%, achieve a nearly 100 times reliability enhancement, and shorten transmission latency by 23.3%. Consequently, a cell-free massive MIMO system with MRC multiuser detection and S-PLD, as a considerable significant potential to facilitate the advancement from URLLC to E2-mURLLC, is promising to support some time-sensitive applications with massive access, such as unmanned aerial vehicles, the Industrial Internet of Things and vehicle-to-vehicle communications.

Channel theory is a fundamental theory of wireless communications. The sixth generation (6G) and beyond 6G (B6G) wireless communication networks are expected to provide space-air-ground-sea global coverage. Base stations and users tend to move in three dimensional (3D) continuous spaces, while antennas and propagation environments can be tightly coupled. The underlying channels show an evolutionary trend to 3D continuous-space radio channels that combine antennas and wireless propagation channels, in comparison to discrete local-space wireless propagation channels in previous generations. This introduces new challenges for channel modeling, channel capacity analysis, antenna design, system design, etc. To address these challenges, this paper performs a comprehensive study on 3D continuous-space radio channels in 6G/B6G with the aid of electromagnetic information theory (EIT) that integrates electromagnetic theory, information theory, wireless propagation channel modeling theory, and antenna theory. We start by revealing the connections and gaps between these four fundamental theories. Then, an in-depth investigation on the four major research thrusts of 3D continuous-space radio channels is provided: 1) channel measurements and modeling, 2) channel capacity analysis, 3) general antenna design, and 4) wireless system design. We aim to explore the intrinsic relationships between antenna parameters, channel parameters, channel characteristics, channel capacity, and communication system performance. Finally, future research directions and challenges for 3D continuous-space radio channels are outlined. Our study endeavors to establish a fundamental framework for 3D continuous-space radio channels, with the potential to catalyze breakthroughs in 6G/B6G theories.

Reliable wireless communications links are a critical but challenging aspect for high speed railway (HSR). To develop and analyze such systems, accurate models for the propagation channel are required. The radio channel properties in HSR scenarios are different from those in cellular scenarios not only due to the high velocity, but also due to the special construction elements and the type of surroundings along the train lines. We performed a measurement campaign at a carrier frequency of 2.4 GHz on the Guangzhou-Shenzhen dedicated high-speed train line in China. Motivated by the results from these measurements, we propose the concept of active scatterer region as an improvement for geometry-based stochastic channel models for HSR, to better describe the non-stationary properties of such channels. Further contributions to the total channel impulse response are also studied, including the line-of-sight component and the scattering component from overhead line poles. Each type of component is modeled and fully parameterized based on the measurement results.

In this paper, the problem of joint power allocation (PA) for the downlink of a multi-cell distributed antenna system (DAS) is addressed. Motivated by practical applications, we focus on a reasonable scenario that only the large-scale channel state information at the transmitter (CSIT) is available. Based on the observation that the capacity-achieving input covariance for each cell is diagonal and that PA optimization is enough to achieve the maximum ergodic sum capacity, we formulate a joint PA optimization problem to maximize the ergodic sum capacity of the system with a total transmit power constraint for each cell. A rather precise closed-form approximation of the ergodic sum capacity is then introduced and taken as the objective function instead so that the original joint PA optimization problem can be simplified. Finally, we propose an iterative PA scheme based on the simplified joint PA optimization problem, in which Signomial Programming (SP) is used. Monte Carlo simulations show that the proposed scheme converges quickly and can offer nearly optimal system ergodic sum capacity. Thus, we refer the proposed PA scheme as a suboptimal one. Moreover, from the simulations we can see that a significant performance gain can be achieved by multi-cell joint PA in DAS with only large-scale CSIT.

We consider transmit rate allocation and the associated cooperative decoding strategies in uplink multi-cell networks where base stations (BSs) are connected by capacity-limited backhaul (BH) links. In particular, we propose two cooperative group decoding (CGD) schemes for the BSs with partial decoding results shared via the BH. In parallel CGD, at each stage, each BS locally selects and jointly decodes a group of users by treating the remaining users as noise; then it forwards some partial decoding results to other BSs via the BH. After subtracting the decoded users and the received decoding results from other BSs, each BS repeats the same procedure until all its designated users are decoded. On the other hand, in sequential CGD, each user can be decoded at any BS. At each stage only one BS is selected to decode a group of users, which then forwards the decoding results to other BSs for interference cancellation. The process is repeated until all users are decoded. Numerical results are provided to demonstrate that the proposed CGD schemes offer significant gain in terms of the achievable rates.