It is supposed that ultra-reliable low latency communication (uRLLC) would continue to evolve in the future sixth generation (6G) network, to provide enhanced capability towards extreme connectivity, with the aid of well established multiple-input multiple-output (MIMO) technology. Since the latency constraint can be represented equivalently by the blocklength of a codeword, channel coding theory at a finite blocklength plays an important role in theoretic analysis of uRLLC. Based on Polyanskiy’s and Yang’s asymptotic results on maximal achievable rate, we first derive the proximate closed-form expressions for the expectation and variance of channel dispersion. Then, the upper bound of average maximal achievable rate is obtained for massive MIMO systems under ideal independent and identically distributed fading channels. Since almost all the fundamental parameters, including the spatial degree-of-freedom (DoF), are considered, this expression can be viewed as a performance bound of the spatiotemporal two-dimension channel coding to some extent. Moreover, it is shown by simulation and analysis, as the DoF goes to infinity, MIMO systems reveal a nature of deterministic transmission, since the average maximal achievable coding rate per antenna can be achieved at each transmission. In this case, the inversely proportional law observed therein implies that the blocklength in the time domain can be further shortened at the expense of spatial DoF. This exchangeability of space and time, to support a given coding rate, paves a solid and feasible road for us to further reduce latency in 6G uRLLC.

Mobile-edge computation offloading (MECO) is a promising emerging technology for battery savings in mobile devices (MD) and/or in latency reduction in the execution of applications by (either total or partial) offloading highly demanding applications from MDs to nearby servers such as base stations. In this paper, we provide an offloading strategy for the joint optimization of the communication and computational resources by considering the blue trade-off between energy consumption and latency. The strategy is formulated as the solution to an optimization problem that minimizes the total energy consumption while satisfying the execution delay limit (or deadline). In the solution, the optimal transmission power and rate and the optimal fraction of the task to be offloaded are analytically derived to meet the optimization objective. We further establish the conditions under which the binary decisions (full-offloading and no offloading) are optimal. We also explore how such system parameters as the latency constraint, task complexity, and local computing power affect the offloading strategy. Finally, the simulation results demonstrate the behavior of the proposed strategy and verify its energy efficiency.

In the sixth generation (6G), ultra-reliable low-latency communications (URLLC) will be further developed to achieve TKμ extreme connectivity. On the premise of ensuring the same rate and reliability, the spatial domain advantage of multiple-input multiple-output (MIMO) has the potential to further shorten the time-domain code length and is expected to be a key enabler for the realization of TKμ. Different coded MIMO schemes exhibit disparities in exploiting the spatial domain characteristics, so we consider two extreme MIMO coding schemes, namely, time-domain coding in which the codewords on multiple spatial channels are independent of each other, and spatiotemporal coding in which multiple spatial channels are jointly coded. By analyzing the statistical characteristics of information density and utilizing the normal approximation, we provide explicit performance bounds for finite blocklength coded MIMO under time-domain coding and spatiotemporal coding. It is found that, different from the phenomenon in time-domain coding where the performance degrades as the blocklengths decrease, spatiotemporal coding can effectively compensate for the performance loss caused by short blocklengths by improving the spatial degrees of freedom (DoF). These results indicate that spatiotemporal coding can fully exploit the spatial dimension advantages of MIMO systems, enabling extremely low error-rate communication under stringent blocklengths constraint.

Current millimeter-wave (mm-Wave) endfire dielectric resonator antennas (DRAs) are limited to single polarization, highlighting the need for dual-polarized operation to fully leverage DRA advantages. Thus, in this letter, a compact dual-polarized endfire DRA array was proposed, and printed circuit board technology is used for high integration. The antenna element is initially designed to incorporate two orthogonal dielectric resonator antenna (DRA) modes, corresponding to vertical polarization (VP) and horizontal polarization (HP) for operation. Furthermore, to enhance the bandwidth of both polarizations, the corresponding cavity mode and slot mode are introduced, which are combined with the corresponding DRA mode for wideband work. VP and HP elements share the same structure, showing a compact size. Based on the element, a four-element array is designed and fabricated. The test results show that an overlapping bandwidth of 24.1-29.6 GHz is realized. Besides, a peak gain of 10.3 and 9.8 dBi for VP and HP is achieved, respectively. Moreover, both VP and HP polarization enable beam scanning. From the above observed characteristics, it can be seen that the proposed design is promising for future 5G mm-Wave terminal applications.

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