With the development of new technologies in the field of renewable energy and batteries, increasing number of houses have been equipped with renewable energy sources (RES) and energy storage systems (ESS) to reduce home energy cost. These houses usually have home energy management systems (HEMS) to control and schedule every electrical device. Various studies have been conducted on HEMS and optimization algorithms for energy cost and peak-to-average ratio (PAR) reduction. However, none of papers give a sufficient study on the utilization of main grid’s electricity and selling electricity. In this paper, firstly, we propose a new HEMS architecture with RES and ESS where we take utilization of the electricity of the main grid and electricity selling into account. With the proposed HEMS, we build general mathematical formulas for energy cost and PAR during a day. We then optimize these formulas using both the particle swarm optimization (PSO) and the binary particle swarm optimization (BPSO). Results clearly show that, with our HEMS system, RES and ESS can help to drop home energy cost significantly to 19.7%, compared with the results of previous works. By increasing charge/discharge rate of ESS, energy cost can be decreased by 4.3% for 0.6 kW and 8.5% for 0.9 kW. Moreover, by using multi-objective optimization, our system can achieve better PAR with an acceptable energy cost.

Two innovative multi-user (MU) communication mechanisms, multi-user multi-input multioutput (MU-MIMO) and orthogonal frequency division multiple access (OFDMA), have recently attracted much attention as key technologies to boost the capabilities of 802.11 Wi-Fi systems. The method of MU transmission in Wi-Fi systems still suffers from severe problems with channel state information (CSI) feedback overhead, however, and this precludes obtaining much higher MU-MIMO gains through user selection. Although in 802.11ax-based Wi-Fi systems the methods used for uplink OFDMA transmission and downlink MU-MIMO transmission bear a great deal of resemblance to each other, in the sense that both are initiated by the AP, this similarity in protocol is not appropriately utilized for close collaboration between the two technologies. This paper proposes MUSE, a novel multi-user transmission scheme for 802.11ax networks. By exploiting uplink OFDMA transmissions for MU-MIMO user selection, MUSE takes advantage of both OFDMA and MU-MIMO functionalities. In particular, the AP estimates and gathers multiple CSI values from the uplink OFDMA frame, and this channel information is then used to find the optimal downlink MU-MIMO receiver group to maximize the system utility. To realize MUSE, a new OFDMA resource allocation algorithm and frame structure are developed. Extensive MATLAB simulation results show that MUSE significantly improves the network throughput, even in dense network scenarios, and also works effectively in co-existence with legacy nodes.

The IEEE 802.11ax standard, which realizes multi-user transmission based on orthogonal frequency division multiple access (OFDMA), has been highlighted as a key technology to meet high future demand for Wi-Fi systems. Since this standard is still being developed, performance analysis through mathematical modeling is of paramount importance; however, existing studies have several limitations. Firstly, most of these consider only the saturation network throughput, whereas for 802.11ax in particular, the access delay of the nodes needs to be studied carefully, since they no longer acquire the medium independently but depend solely on the access point’s (AP’s) schedule. Secondly, since the network performance may be affected to a greater extent by legacy nodes than by 802.11ax nodes, it is desirable to consider various heterogeneous cases of networks with existing legacy nodes. In this paper, a new analytical framework for the 802.11ax MAC protocol is provided. Markov-chain-based models are developed to represent the behavior of the 802.11ax nodes, and both non-saturated traffic conditions and co-existence with the legacy nodes are considered. Through both analysis and MATLAB simulations, it is shown that the proposed model accurately evaluates the throughput and the delay performance under various network conditions.

This letter provides a comprehensive analytic framework for the full-duplex MAC protocol. First, to the best of our knowledge, we develop the first full-duplex model that practically considers non-saturated traffic conditions. Second, we examine all types of full-duplex transmissions, namely, asymmetric and symmetric transmissions. Through both analysis and simulations, we show that our analytic model accurately evaluates the throughput and delay performance for all types of full-duplex transmissions in non-saturated conditions.