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The compressive sensing (CS) based sparse vector coding (SVC) method is one of the promising ways for the next-generation ultra-reliable and low-latency communications. In this paper, we present advanced algorithm-hardware co-optimization schemes for realizing a cost-effective SVC decoding architecture. The previous maximum a posteriori subspace pursuit (MAP-SP) algorithm is newly modified to relax the computational overheads by applying novel residual forwarding and LLR approximation schemes. A fully-pipelined parallel hardware is also developed to support the modified decoding algorithm, reducing the overall processing latency, especially at the support identification step. In addition, an advanced least-square-problem solver is presented by utilizing the parallel Cholesky decomposer design, further reducing the decoding latency with parallel updates of support values. The implementation results from a 22nm FinFET technology showed that the fully-optimized design is 9.6 times faster while improving the area efficiency by 12 times compared to the baseline realization. [ABSTRACT FROM AUTHOR]

Nowadays low voltage SVG (Static Var Generator) has got a certain amount of practical applications. Current PWM control is a key unit of SVG control process. Taking the three-phase four-leg inverter for research object, this paper designs the current controller base on one-cycle control algorithm and derivates the control equation in detail. Aimed at the problem of control shocks existing in traditional one-cycle control, the improved control unit is given out with the fundamental positive sequence active component of load current as control objectives. This improved control unit could realize reactive power, harmonics, and negative sequence imbalance current comprehensive compensation function, and duty cycle stability are improved. Control performance and response time of the control unit were significantly optimized. The proposed improved one-cycle control unit was validated in terms of simulation and experiment result, and has high practical value of low-voltage SVG application. [ABSTRACT FROM AUTHOR]

Purpose The loading and power variations in the power system, especially for the peak hours have abundant concussion on the loading patterns of the open access transmission system. During such unconditional state of loading the transmission line parameters and the line voltages show a substandard profile, which depicts exaction of congestion management of the power line in such events. The purpose of this paper is to present an uncomplicated and economical model for congestion management using flexible AC transmission system (FACTS) devices.Design/methodology/approach The approach desires a two-step procedure, first by optimal placement of thyristor controlled series capacitor (TCSC) and static VAR compensator (SVC) as FACTS devices in the network; second tuning the control parameters to their optimized values. The optimal location and tuning of TCSC and SVC represents a hectic optimization problem, due to its multi-objective and constrained nature. Hence, a reassuring heuristic optimization algorithm inspired by behavior of cat and firefly is employed to find the optimal placement and tuning of TCSC and SVC.Findings The effectiveness of the proposed model is tested through simulation on standard IEEE 14-bus system. The proposed approach proves to be better than the earlier existing approaches in the literature.Research limitations/implications With the completed simulation and results, it is proved that the proposed scheme has reduced the congestion in line, thereby increasing the voltage stability along with improved loading capability for the congested lines.Practical implications The usefulness of the proposed scheme is justified with the computed results, giving convenience for implementation to any practical transmission network.Originality/value This paper fulfills an identified need to study exaction of congestion management of the power line. [ABSTRACT FROM AUTHOR]