To meet the stringent high-throughput demands of enhanced mobile broadband (eMBB), low-density parity-check (LDPC) decoding is limited to few iterations. This constraint usually degrades error-correcting performance, rousing a critical need for puncturing towards algorithmic enhancements. However, existing puncturing methods lack modulation and rate compatibility, converging to local optima due to greedy search strategies. To this end, this paper proposes a modulation and rate compatible puncturing (MrcPunc) for 5G LDPC codes. It incorporates three key techniques: 1)a revised protograph-based extrinsic information transfer (PEXIT) analysisfor accurate performance prediction, 2)a progressive multi-path search (PMPS) algorithmto avoid local optima, and 3)a compatibility optimizationsupporting various modulations and code rates. The MrcPunc yields up to 0.6 dB gain over the 5G standard puncturing under few-iteration condition without extra decoding complexity. It is noted that MrcPunc guarantees robustness against both larger iteration counts and mismatched modulations, alongside reducing the average number of decoding iterations.

This paper proposes an optimal dynamic supply of parking permits under uncertainties in the mixed traffic environment of regular vehicles (RVs) and autonomous vehicles (AVs). The uncertainties from queuing delay and cruising-for-parking time, respectively, are derived from parking permit holders’ unascertainable early arrival/late departure and the randomness of vehicle speed for cruising-for-parking users. We formulate the dynamic system optimum as a stochastic optimal control problem, aiming to minimize the total time lost for all parking users. On this basis, we express the optimality condition as Hamilton-Jacobi-Bellman equation and propose an optimal control strategy for dynamic supply of parking permits (called optimal parking supply scheme). The proposed scheme is determined by two observable and measurable variables, i.e., queuing time and cruising-for-parking time. We find that the scheme can significantly reduce the total system time lost, especially when the uncertainty from parking permit holders is at a high level or the percentage of AVs is small. Finally, a case study of a selected sample area in Beijing is conducted, which verifies the efficiency of the proposed scheme numerically.

Dynamic Voltage Restorer (DVR), as a device of voltage sag compensation, demands fast transient response, and the disturbance of source voltage is a main impact on control performance. The DVR control strategy based on discrete state space will enhance control bandwidth and stability. However, for the discrete space control system, the number of parameters is relatively more which will lead to a complicated design process. To solve this problem, this paper proposed a control parameter design method based on the idea of virtual resistor. Firstly, by means of state feedback control, an adjustable virtual resistor can be series in filter inductor. According to the requirements of steady-state error, phase margin and Routh's criterion in w domain, the variation regions of PI parameters and virtual resistance can be solved by a step-by-step method, and then the appropriate control parameters can be selected. Experimental results from a digital signal processor-based system are included to support theoretical analysis.