The Internet of Things (IoT) extends network connectivity and computing capability to physical devices. However, data from IoT devices may increase the risk of privacy violations. In this paper, we consider smart meters as a prominent early instance of the IoT, and we investigate their privacy protection solutions at customer premises. In particular, we design a load hiding approach that obscures household consumption with the help of energy storage units. For this purpose, we leverage the opportunistic use of existing household energy storage units to render load hiding less costly. We propose combining the use of electric vehicles (EVs) and heating, ventilating, and air conditioning (HVAC) systems to reduce or eliminate the reliance on local rechargeable batteries for load hiding. To this end, we formulate a Markov decision process to account for the stochastic nature of customer demand and use a Q-learning algorithm to adapt the control policies for the energy storage units. We also provide an idealized benchmark system by formulating a deterministic optimization problem and deriving its equivalent convex form. We evaluate the performance of our approach for different combinations of storage units and with different benchmark methods. Our results show that the opportunistic joint use of EV and HVAC units can reduce the need of dedicated large-capacity or fast-charging-cycle batteries for load hiding.

Non-orthogonal multiple access (NOMA) is being considered as a primary candidate to address the challenge of massive connectivity in the fifth generation (5G) wireless communication systems. In this letter, we propose a low-complexity NOMA mechanism with efficient multi-user detection (MUD) based on the adaptive alternating direction method of multipliers (ADMM), which is able to jointly detect user activity and transmitted data. The proposed algorithm leverages the transmit symbol estimate and active user set as “prior knowledge”, which can be obtained from the previous iterations/time intervals, for improved MUD performance. We demonstrate that our proposed mechanism outperforms the state-of-art MUD NOMA schemes.

Visible light communication (VLC) turns indoor light-emitting diode (LED)-based illumination devices into high-speed network portals that, for example, operate in tandem with existing Wi-Fi networks. Since in this scenario, multiple VLC-equipped luminaires would serve overlapping service areas, we suggest the use of power line communication (PLC) to coordinate and provide data to the VLC transmitters. In particular, in this paper, we propose a hybrid VLC-PLC (HVP) system architecture for the indoor downlink transmission and present the analytical framework for the data rate analysis of the HVP system. In our solution, spatial optical OFDM (SO-OFDM) is applied across multiple luminaires, for which we propose several subcarrier allocation schemes to exploit the frequency selectivity of the VLC and PLC channels. Different possible and meaningful variations of the HVP system, including the choice of optical OFDM transmission, relay, and multiple access schemes, are investigated and compared. The numerical results establish achievable rates for relevant communication scenarios and highlight the advantages of the proposed subcarrier allocation scheme in terms of rate and reduced peak power of optical OFDM signals.

Bit-interleaved coded modulation (BICM) has become the de facto coding standard for communication systems. Recently, BICM has been cast as a mismatched decoding scheme due to the assumption of independent bit metrics. In addition to this inherent mismatch, practical demodulators may produce mismatched decoding metrics because of implementation constraints, such as clipping and metric approximation to reduce computational complexity. In this paper, we investigate BICM with such metrics. In line with recent works on this topic, we adopt the generalized mutual information (GMI) as the pertinent performance measure. First, we show that level-dependent scaling of logarithmic bit metrics can improve the BICM GMI. Second, we propose a uniform metric scaling which can lead to an improved performance of mismatched sum-product symbol-by-symbol decoding, even if the GMI is not changed. Third, we investigate general metric-mismatch correction methods and analyze their effects in terms of the GMI. By means of three application examples, we illustrate that metric-mismatch correction, including metric scaling, can significantly increase BICM rates.

Remote monitoring of electrical cable conditions is an essential characteristic of the next-generation smart grid, which features the ability to consistently surveil and control the grid infrastructure. In this paper, we propose a technique that harnesses power line modems (PLMs) for monitoring cable health. We envisage that all or most of these PLMs have already been deployed for data communication purposes and focus on the distribution grid or neighborhood area networks in the smart grid. For such a setting, we propose a machine learning (ML) based framework for automatic cable diagnostics by continuously monitoring the cable status to identify, assess, and locate possible degradations. As part of our technique, we also synthesize state-of-the-art reflectometry methods within the PLMs to extract beneficial features for effective performance of our proposed ML solution. Simulation results demonstrate the effectiveness of our solution under different aging conditions and varying load configurations. Finally, we reflect on our proposed diagnostics method by evaluating its robustness and comparing it with existing alternatives.

Visible light communication (VLC) is an emerging short-range optical wireless communication technology that is driven by the widespread deployment of light-emitting diodes (LEDs). Indoor VLC users may experience noticeable interference when independent transmitters utilizing wide-beam luminaires are closely located. In this paper, a coordinated beamforming (CB) scheme is proposed for downlink interference mitigation among coexisting VLC attocells utilizing multi-luminaire transmitters. Compared to joint transmission (JT) schemes, wherein the data and channel state information are shared among transmitters of different attocells, the proposed CB scheme places lower requirements on the network in terms of backbone traffic, and is easier to implement in a practical deployment, though at the cost of compromised performance. In this paper, we investigate the downlink transmission of coordinated VLC attocells and focus on its transmitter design. The weighted sum mean square error (WSMSE) is adopted as the performance metric to take into consideration interference, noise, and fairness among users in system optimization. The WSMSE minimization problem is considered with linear beamforming restricted by amplitude constraints. Such constraints arise from dynamic range limitations in typical LEDs. Moreover, we extend our design method to take into account possible mismatches in channel information available to the transmitters. Numerical examples are provided to illustrate the performance of the proposed CB scheme in typical VLC scenarios. We also quantify the performance gap among several coordination schemes including JT and CB.