No abstract

Device-to-device (D2D) communication has the potential to facilitate wireless multicast by retransmissions among users in proximity to each other. In this paper, the D2D assisted cooperative multicast (CM) is investigated in a new scenario, where a large number multicast recipients are densely distributed within a small area (called a D2D cluster). In this scenario, D2D multicast is innovatively employed in the retransmission stage, and a new relay selection scheme named nearest center protocol (NCP) is proposed. Moreover, the optimal time allocation between the two transmission stages is investigated, with the aim of minimizing the total time consumption of the two-stage CM. The time allocation problem is then formulated as an optimization problem and solved by the sequential quadratic programming (SQP) method. Simulation results show that the D2D assisted two-stage CM can achieve higher cost-efficiency than the conventional one-stage multicast, and the gain becomes larger when the D2D cluster moves farther from BS. Besides, the optimal time allocation between the two transmission stages also varies with the location of the D2D cluster, which means equal time allocation is no longer appropriate to be used in our new scenario.

Energy efficiency (EE) has become an increasingly important issue in Device-to-Device (D2D) communications since wireless terminals are hand-held equipments with limited battery life. In this paper, an energy-efficient channel reusing scheme for multi-D2D links is proposed. We first analyze the EE of a single D2D link in both non-cooperative mode (NCM) and cooperative mode (CM), and prove that the EE of the D2D link is mainly determined by the location of the cellular user equipment (CUE) that shares resource with the D2D pair. On this basis, a locationbased algorithm (LBA) is proposed to select the optimal CUE for each of the D2D pairs, aiming to maximize the sum EE of all D2D links. Numerical results show that the proposed LBA could effectively improve the overall EE of the D2D system while guaranteeing the target rate of each D2D link. Moreover, the proposed LBA does not require the channel state information (CSI) of all the involved links, which could significantly reduce the feedback overhead and computational complexity.

Clustering is a promising interference mitigation scheme in dynamic TDD systems. However, most previous works just took large-scale path loss or coupling loss as criteria of the clustering schemes, thus the throughput performance would be limited by the varying traffic requirements among different small cells within one cluster. In this paper, a novel dynamic clusterbased Interference Mitigation and Traffic Adaptation (IMTA) scheme is proposed and evaluated with dense deployment of small cells (SCs). Firstly, a new clustering criterion named Differentiating Metric (DM) is defined. Based on the defined DM value, a DM matrix is formed and further presented by a clustering graph. In the clustering graph, the dynamic clustering strategy is mapped to a MAX K-CUT problem, which is addressed in polynomial time by a proposed heuristic clustering algorithm. Furthermore, the system level simulation results demonstrate a promising improvement on uplink traffic throughput (UTP) in our proposed scheme compared with traditional clustering schemes.

Because of the limitation of Fast Fourier Transform(FFT) for the methed of traditional spectrum analysis to analyze the unsteady signal, wavelet analysis are made for the typical unsteady process signal of starting up and shut down with the good characteristic of simultaneous localization in both the time and the frequency domains based on the field test, in which the signal is decomposed into different frequency band, and then the weak signal is caught and the dominant frequency is picked up for the analysis of the vibration source. It proved that the wavelet is a most powerful tool for processing the unsteady signal.