Sangarapillai Lambotharan

Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities

Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and smart metering. In particular, we focus on some of the key communications challenges for realizing interoperable and future-proof smart grid/metering networks, smart grid security and privacy, and how some of the existing networking technologies can be applied to energy management. Finally, we also discuss the coordinated standardization efforts in Europe to harmonize communications standards and protocols.

An integer linear programming based optimization for home demand-side management in smart grid

We propose a consumption scheduling mechanism for home area load management in smart grid using integer linear programming (ILP) technique. The aim of the proposed scheduling is to minimise the peak hourly load in order to achieve an optimal (balanced) daily load schedule. The proposed mechanism is able to schedule both the optimal power and the optimal operation time for power-shiftable appliances and time-shiftable appliances respectively according to the power consumption patterns of all the individual appliances. Simulation results based on home and neighbourhood area scenarios have been presented to demonstrate the effectiveness of the proposed technique.

Effective capacity for interference and delay constrained cognitive radio relay channels

This paper investigates delay constrained performance of a cognitive radio relay network when the cognitive (secondary) user transmission is subject to satisfying spectrum-sharing restrictions imposed by a primary user. The primary user allows a secondary user to gain access to its allocated spectrum band as long as certain thresholds on the interference power, on the peak or average values, inflicted on the primary receiver are not exceeded by the transmission of the secondary users. In addition, we assume that the secondary transmitter benefits from an intermediate node, chosen from K terminals, to relay its signal to the destination. Considering that the transmission of the secondary user is subject to satisfying a statistical delay quality-of-service (QoS) constraint, we study the maximum arrival rate of the secondary users relay link while the interference limitations required by the primary user are satisfied. Particularly, we obtain the effective capacity of the secondary network and determine the power allocation policies that maximize the effective capacity of the secondary users relaying channel. In addition, we derive closed-form expressions for the effective capacity of the channel in Rayleigh block-fading environment under peak or average interference-power constraints. Numerical simulations are provided to endorse our theoretical results.

A Cooperative MMSE Relay Strategy for Wireless Sensor Networks

We propose a minimum mean-square error (MMSE)-based signal forwarding technique for a cooperative relay network. Transmission of information between multiple source-destination pairs through a set of relays is considered. Cooperation between relays has been shown to improve substantially the bit-error rate (BER) performance as compared to noncooperative relays under a total power constraint. A general model for relay cooperation has been considered; however, for a single source-destination scenario, the proposed MMSE relaying strategy has been shown to be a product of receiver and transmitter beamformers at the relay layer.

Interference Alignment Techniques for MIMO Multi-Cell Interfering Broadcast Channels

The interference alignment (IA) is a promising technique to efficiently mitigate interference and to enhance capacity of a wireless communication network. This paper proposes an interference alignment scheme for a network with multiple cells and multiple multiple-input and multiple-output (MIMO) users under a Gaussian interference broadcast channel (IFBC) scenario. We first extend a grouping method already known in the literature to a multiple-cells scenario and jointly design transmit and receiver beamforming vectors using a closed-form expression without iterative computation. Then we propose a new approach using the principle of multiple access channel (MAC) - broadcast channel (BC) duality to perform interference alignment while maximizing capacity of users in each cell. The algorithm in its dual form is solved using interior point methods. We show that the proposed approach outperforms the extension of the grouping method in terms of capacity and basestation complexity. Finally, a rate balancing technique is introduced to maintain fairness among users.

SINR Balancing Technique for Downlink Beamforming in Cognitive Radio Networks

We propose a novel signal to interference and noise (SINR) balancing technique for a downlink cognitive radio network (CRN) wherein multiple cognitive users (also referred to as secondary users (SUs)) coexist and share the licensed spectrum with the primary users (PUs) using the underlay approach. The proposed beamforming technique maximizes the worst SU SINR while ensuring that the interference leakage to PUs is below specific thresholds. Due to the additional interference constraints imposed by PUs, the principle of uplink-downlink duality used in the conventional downlink beamformer design cannot be directly applied anymore. To circumvent this problem, using an algebraic manipulation on the interference constraints, we propose a novel SINR balancing technique for CRNs based on uplink-downlink iterative design techniques. Simulation results illustrate the convergence and the optimality of the proposed beamformer design.

Closed-loop quasi-orthogonal STBCs and their performance in multipath fading environments and when combined with turbo codes

Quasi-orthogonal space-time block codes (QO-STBCs) achieve full code rate at the expense of loss in diversity gain. We propose two feedback methods for QO-STBCs to achieve full diversity and full code rate. In the first method, signals radiated from various antennas are rotated by phasors according to feedback from the receiver, whereas the second method is based upon antenna weighting/selection. For high to moderate feedback error rates, it is demonstrated that the proposed methods outperform the quantized transmit beamformer. The performance improvement is also investigated for these closed-loop methods when the transmitted signal is error control coded.

Overview of demand management in smart grid and enabling wireless communication technologies

There are significant challenges as well as great opportunities for research at both policy and technology levels on the efficient use of energy. Most existing power generation and distribution systems are based on a century old mechanism where power grids are managed by vertically integrated utilities. Intelligent power grids known as smart grids are required as the demand for energy continues to grow and more and more emphasis is being placed on the supply of renewable energy. The main ingredient of smart grids is the integration of information and communication technology (ICT) into the grids to monitor and regulate power generation and demand. This article provides an overview of demand management with a particular focus on the necessary enabling wireless technologies. Various mechanisms and algorithms for the optimal demand management in smart grids using these wireless technologies are also reviewed.

An integer linear programming and game theory based optimization for demand-side management in smart grid

We propose a consumption scheduling mechanism for home and neighbourhood area load demand management in smart grid using integer linear programming (ILP) and game theory. The proposed mechanism is able to schedule both the optimal power and the optimal operation time for power-shiftable appliances and time-shiftable appliances respectively according to the power consumption patterns of all the individual appliances. Simulation results for both the centralised and the distributed management scenarios have been presented to demonstrate and verify the effectiveness of the proposed technique.

Joint Beamforming and User Maximization Techniques for Cognitive Radio Networks Based on Branch and Bound Method

We consider a network of cognitive users (also referred to as secondary users (SUs)) coexisting and sharing the spectrum with primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we consider a CRN wherein the number of SUs requesting channel access exceeds the number of available frequency bands and spatial modes. In such a setting, we propose a joint fast optimal resource allocation and beamforming algorithm to accommodate maximum possible number of SUs while satisfying quality of service (QoS) requirement for each admitted SU, transmit power limitation at the secondary network basestation (SNBS) and interference constraints imposed by the PUs. Recognizing that the original user maximization problem is a nondeterministic polynomial-time hard (NP), we use a mixed-integer programming framework to formulate the joint user maximization and beamforming problem. Subsequently, an optimal algorithm based on branch and bound (BnB) method has been proposed. In addition, we propose a suboptimal algorithm based on BnB method to reduce the complexity of the proposed algorithm. Specifically, the suboptimal algorithm has been developed based on the first feasible solution it achieves in the fast optimal BnB method. Simulation results have been provided to compare the performance of the optimal and suboptimal algorithms.