Loading-balance relay-selective strategy based on stochastic dynamic program

Abstract

A Relay-Assisted (RA) network with relay selection is considered as a type of effective technology to improve the spectrum and energy efficiency of a cellular network. However, loading balance of the assisted relay node becomes an inevitable bottleneck in RA network development because users do not follow uniform distribution. Furthermore, the time-varying channel condition of wireless communication is also a major challenge for the RA network with relay selection. To solve these problems and improve the practicability of the RA network, a Loading Balance-Relay Selective (LBRS) strategy is proposed for the RA network in this paper. The proposed LBRS strategy formulates the relay selection of the RA network under imperfect channel state information assumption as a Multistage Decision (MD) problem. An optimal algorithm is also investigated to solve the proposed MD problem based on stochastic dynamic program. Numerical results show that the performance of the LBRS strategy is better than that of traditional greedy algorithm and the former is effective as an exhaustive search-based method.

Dispatch of a Coal Mine-Integrated Energy System: Optimization Model with Interval Variables and Lower Carbon Emission

“…The underground wastewater influx is closely related to climate, hydrology, landforms, and mining schedules [28] . The temperature of geothermal energy to be released can be increased along with the mining depth, and the amount of geothermal release is also influenced by environmental factors such as season and climate [29] . In summary, CMAE has great uncertainties and volatilities, which must be carefully treated in the dispatching process.…”

“…Model with Interval Uncertainty As addressed in Section 3, in our dispatch model, the variables to be optimized include two parts, crisp variables as and the other is the interval ones as , which greatly differ from those in traditional interval dispatch models, as described in Ref. [29]. For traditional interval dispatch models, the intervals are usually known parameters, i.e., the upper and lower limits are determined, and the variables to be optimized are only crisp values in such an interval.…”

Efficient static compaction of test patterns using partial maximum satisfiability

“…Last, the SAFs aims at a single fault in the chip, while existing experiments have shown that the test set that can cover all single faults also has a high coverage rate when multiple faults are being detected [22] . For the generated PMS formulas, SATLike, which is a famous incomplete partial MaxSAT solver based on the dynamic local search [23] approach, is selected in Step (6). In terms of the new set of test patterns, Step (7) confirms that the fault coverage will not decrease.…”