Yuzhe Xu

Real-time scheduling in LTE for smart grids

The latest wireless network, 3GPP Long Term Evolution (LTE), is considered to be a promising solution for smart grids because it provides both low latency and large bandwidth. However, LTE was not originally intended for smart grids applications, where data generated by the grid have specific delay requirements that are different from traditional data or voice communications. In this paper, the specific requirements imposed by a smart grids on the LTE communication infrastructure is first determined. The latency offered by the LTE network to smart grids components is investigated and an empirical mathematical model of the distribution of the latency is established. It is shown by experimental results that with the current LTE up-link scheduler, smart grid latency requirements are not always satisfied and that only a limited number of components can be accommodated. To overcome such a deficiency, a new scheduler of the LTE medium access control is proposed for smart grids. The scheduler is based on a mathematical linear optimization problem that considers simultaneously both the smart grid components and common user equipments. An algorithm for the solution to such a problem is derived based on a theoretical analysis. Simulation results based on this new scheduler illustrate the analysis. It is concluded that LTE can be effectively used in smart grids if new schedulers are employed for improving latency.

A Virtual Laboratory for Micro-Grid information and communication infrastructures

Testing smart grid information and communication (ICT) infrastructures is imperative to ensure that they meet industry requirements and standards and do not compromise the grid reliability. Within the micro-grid, this requires identifying and testing ICT infrastructures for communication between distributed energy resources, building, substations, etc. To evaluate various ICT infrastructures for micro-grid deployment, this work introduces the Virtual Micro-Grid Laboratory (VMGL) and provides a preliminary analysis of Long-Term Evolution (LTE) as a micro-grid communication infrastructure.

Distributed association control and relaying in millimeter wave wireless networks

Millimeter wave (mmWave) spectrum is one of the frontiers in the evolution towards the next generation of the wireless communication systems, which can provide great performance benefits at the variform access and backbone networks. However, at the access level the typical rapidly fading behavior of the mmWave channel imposes the careful design of client association to access points (APs), as well as relaying to other clients, which can act as bridge toward the APs. This challenge is hereby addressed by a distributed approach that optimally solves the joint client association and relaying problem. The problem is posed as a novel multi-dimensional assignment problem, for which an original solution method is established by a series of transformations that lead to a tractable minimum cost flow problem. The method allows to design distributed auction algorithms where the clients and relays act asynchronously to achieve optimal client-relay-AP association. It is shown that the algorithms converge to a solution that maximizes the total network throughput within a desired bound.

Distributed spectral efficiency maximization in full-duplex cellular networks

Three-node full-duplex is a promising new transmission mode between a full-duplex capable wireless node and two other wireless nodes that use half-duplex transmission and reception respectively. Although three-node full-duplex transmissions can increase the spectral efficiency without requiring full-duplex capability of user devices, inter-node interference - in addition to the inherent self-interference - can severely degrade the performance. Therefore, as methods that provide effective self-interference mitigation evolve, the management of internode interference is becoming increasingly important. This paper considers a cellular system in which a full-duplex capable base station serves a set of half-duplex capable users. As the spectral efficiencies achieved by the uplink and downlink transmissions are inherently intertwined, the objective is to device channel assignment and power control algorithms that maximize the weighted sum of the uplink-downlink transmissions. To this end a distributed auction based channel assignment algorithm is proposed, in which the scheduled uplink users and the base station jointly determine the set of downlink users for full-duplex transmission. Realistic system simulations indicate that the spectral efficiency can be up to 89% better than using the traditional half-duplex mode. Furthermore, when the self-interference cancelling level is high, the impact of the user-to-user interference is severe unless properly managed.

Distributed Association and Relaying With Fairness in Millimeter Wave Networks

Millimeter wave (mmWave) systems are emerging as an essential technology for enabling extremely high data rate wireless communications. The main limiting factors of mmWave systems are blockage (high penetration loss) and deafness (misalignment between the beams of the transmitter and receiver). To alleviate these problems, it is imperative to incorporate efficient association and relaying between terminals and access points. Unfortunately, the existing association techniques are designed for the traditional interference-limited networks, and thus are highly suboptimal for mmWave communications due to narrow-beam operations and the resulting non-negligible interference-free behavior. This paper introduces a distributed approach that solves the joint association and relaying problem in mmWave networks considering the load balancing at access points. The problem is posed as a novel stochastic optimization problem, which is solved by distributed auction algorithms where the clients and relays act asynchronously to achieve optimal client-relay-access point association. It is shown that the algorithms provably converge to a solution that maximizes the aggregate logarithmic utility within a desired bound. Numerical results allow quantification of the performance enhancements introduced by the relays, and the substantial improvements of the network throughput and fairness among the clients by the proposed association method as compared to standard approaches. It is concluded that mmWave communications with proper association and relaying mechanisms can support extremely high data rates, connection reliability, and fairness among the clients.

User association and the alignment-throughput tradeoff in millimeter wave networks

Millimeter wave (mmWave) communication is a promising candidate for future extremely high data rate, wireless networks. The main challenges of mmWave communications are deafness (misalignment between the beams of the transmitter and receiver) and blockage (severe attenuation due to obstacles). Due to deafness, prior to link establishment between a client and its access point, a time consuming alignment/beam training procedure is necessary, whose complexity depends on the operating beamwidth. Addressing blockage may require a reassociation to non-blocked access points, which in turn imposes additional alignment overhead. This paper introduces a unifying framework to maximize network throughput considering both deafness and blockage. A distributed auction-based solution is proposed, where the clients and access points act asynchronously to achieve optimal association along with the optimal operating beamwidth. It is shown that the proposed algorithm provably converges to a solution that maximizes the aggregate network utility within a desired bound. Convergence time and performance bounds are derived in closed-forms. Numerical results confirm superior throughput performance of the proposed solution compared to existing approaches, and highlight the existence of a tradeoff between alignment overhead and achievable throughput that affects the optimal association.

Distributed Spectrum Leasing via Vertical Cooperation in Cognitive Radio Networks

In hierarchical cognitive radio networks, unlicensed secondary users can increase their achievable rates by assisting licensed primary user transmissions via cooperation. In this paper, a novel approach to maximizing the transmission rates in the secondary network by optimizing the relay selection, the secondary transmit powers, and the cooperative relaying power splitting parameters is proposed. The resulting optimization problem is mixed integer and nonconvex, which makes it NP hard to find the optimal solutions. Therefore, centralized and distributed solution methods to find near-to-optimal solutions of this challenging problem are proposed. The methods are based on iteratively solving the secondary relay selection by a greedy approach, and the optimal power allocation problem by a fixed-point approach together with alternating direction method of multipliers. It is established that both centralized and distributed solution methods always converge. The numerical results illustrate how the performance of the proposed solution methods depend on the primary performance margins, and show that they give a near-to-optimal solution in few iterations.

A distributed pareto-optimal dynamic estimation method

In this paper, a novel distributed model-based prediction method is proposed using sensor networks. Each sensor communicates with the neighboring nodes for state estimation based on a consensus protocol without centralized coordination. The proposed distributed estimator consists of a consensus-filtering scheme, which uses a weighted combination of sensors information, and a model-based predictor. Both the consensus-filtering weights and the model-based prediction parameter for all the state components are jointly optimized to minimize the variance and bias of the prediction error in a Pareto framework. It is assumed that the weights of the consensus-filtering phase are unequal for the different state components, unlike consensus-based approaches from literature. The state, the measurements, and the noise components are assumed to be individually correlated, but no probability distribution knowledge is assumed for the noise variables. The optimal weights are derived and it is established that the consensus-filtering weights and the model-based prediction parameters cannot be designed separately in an optimal way. The asymptotic convergence of the mean of the prediction error is demonstrated. Simulation results show the performance of the proposed method, obtaining better results than distributed Kalman filtering.

Auction Based Dynamic Distributed Association in Millimeter Wave Networks

Special characteristics of millimeter wave (mmWave) systems such as high vulnerability to random obstacles (due to high penetration loss) and mobility (due to directional communications) demand redesigning the existing algorithms or the association between clients and access points. In this paper, we propose a novel dynamic association scheme, based on the distributed auction algorithm, that is robust to variations of the mmWave wireless channel and to mobility of client. In particular, the resulting optimal association solution does not have to be re-computed every time the network changes (e.g., due to mobility). Instead, the algorithm continuously adapt to the network variation and is thus very efficient. Numerical analysis verifies the ability of the proposed algorithms to optimize the association and to maintain optimality in dynamic environments of mmWave networks.

Chapter 25 – Distributed Estimation ☆

Distributed estimation plays an essential role in many networked applications, such as communication, networked control, monitoring, and surveillance. Motivated by this, the chapter provides an overview on some of the fundamental aspects of distributed estimation over networks together with an investigation of the computational complexity and communication cost. A phenomenon being observed by a number of sensors in networks having a star and a general topology are considered. Under the assumptions of noises and linear measurements, the resulting distributed estimators are derived respectively. The limited bandwidth, communication range, and message loss in the communication are considered. Distributed estimators can provide accurate estimates of the parameters of the phenomenon, while the less the limitations are in networks, the lower complexity of the estimator is.