LAUSR

The spectrum-sharing access technology using unlicensed spectrum bands is considered as a promising solution to solve the spectrum deficiency problem for various Internet of Things services. But, the efficient and fairness-guaranteed spectrum-sharing access among different systems is challenging by using the listen-before-talk (LBT) technology due to the uncertain channel quality and the channel access collision issues in unlicensed spectrum bands. To solve these problems, a novel three dimension-based Markov chain model is designed to formulate the collision probability of the spectrum-sharing access process using the contention window (CW) back-off algorithm based on the channel quality indicator feedback information. The key reasons for the packet transmission failure are comprehensively analyzed by considering both the channel collision and the channel quality deterioration conditions. A fairness-based spectrum-sharing access algorithm is proposed by assigning the optimal CW for the LBT system to minimize the collision probability and guarantee the fairness among LBT and wireless fidelity coexisted systems. Hardware platform-based evaluation results prove that our proposed algorithms can improve the system throughput and guarantee the fairness among different systems in the unlicensed spectrum band.