arXiv subjects

Tony Q. S. Quek

Publications and source records attributed to Tony Q. S. Quek.

317 records · Page 18Linked to original sources

arXiv2015

Heterogeneous Cellular Networks Using Wireless Backhaul: Fast Admission Control and Large System Analysis

We consider a heterogeneous cellular network with densely underlaid small cell access points (SAPs). Wireless backhaul provides the data connection from the core network to SAPs. To serve as many SAPs and their corresponding users as possible with guaranteed data rates, admission control of SAPs needs to be performed in wireless backhaul. Such a problem involves joint design of transmit beamformers, power control, and selection of SAPs. In order to tackle such a difficult problem, we apply $\ell_1$-relaxation and propose an iterative algorithm for the $\ell_1$-relaxed problem. The selection of SAPs is made based on the outputs of the iterative algorithm. This algorithm is fast and enjoys low complexity for small-to-medium sized systems. However, its solution depends on the actual channel state information, and resuming the algorithm for each new channel realization may be unrealistic for large systems. Therefore, we make use of random matrix theory and also propose an iterative algorithm for large systems. Such a large system iterative algorithm produces asymptotically optimum solution for the $\ell_1$-relaxed problem, which only requires large-scale channel coefficients irrespective of the actual channel realization. Near optimum results are achieved by our proposed algorithms in simulations.

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arXiv2015

D2D Enhanced Heterogeneous Cellular Networks with Dynamic TDD

Over the last decade, the growing amount of UL and DL mobile data traffic has been characterized by substantial asymmetry and time variations. Dynamic time-division duplex (TDD) has the capability to accommodate to the traffic asymmetry by adapting the UL/DL configuration to the current traffic demands. In this work, we study a two-tier heterogeneous cellular network (HCN) where the macro tier and small cell tier operate according to a dynamic TDD scheme on orthogonal frequency bands. To offload the network infrastructure, mobile users in proximity can engage in D2D communications, whose activity is determined by a carrier sensing multiple access (CSMA) scheme to protect the ongoing infrastructure-based and D2D transmissions. We present an analytical framework to evaluate the network performance in terms of load-aware coverage probability and network throughput. The proposed framework allows to quantify the effect on the coverage probability of the most important TDD system parameters, such as the UL/DL configuration, the base station density, and the bias factor. In addition, we evaluate how the bandwidth partition and the D2D network access scheme affect the total network throughput. Through the study of the tradeoff between coverage probability and D2D user activity, we provide guidelines for the optimal design of D2D network access.

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arXiv2015

Hybrid Full-/Half-Duplex System Analysis in Heterogeneous Wireless Networks

Full-duplex (FD) radio has been introduced for bidirectional communications on the same temporal and spectral resources so as to maximize spectral efficiency. In this paper, motivated by the recent advances in FD radios, we provide a foundation for hybrid-duplex heterogeneous networks (HDHNs), composed of multi-tier networks with a mixture of access points (APs), operating either in bidirectional FD mode or downlink half-duplex (HD) mode. Specifically, we characterize the net- work interference from FD-mode cells, and derive the HDHN throughput by accounting for AP spatial density, self-interference cancellation (IC) capability, and transmission power of APs and users. By quantifying the HDHN throughput, we present the effect of network parameters and the self-IC capability on the HDHN throughput, and show the superiority of FD mode for larger AP densities (i.e., larger network interference and shorter communication distance) or higher self-IC capability. Furthermore, our results show operating all APs in FD or HD achieves higher throughput compared to the mixture of two mode APs in each tier network, and introducing hybrid-duplex for different tier networks improves the heterogenous network throughput.

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arXiv2015

Robust Decentralized Detection and Social Learning in Tandem Networks

We study a tandem of agents who make decisions about an underlying binary hypothesis, where the distribution of the agent observations under each hypothesis comes from an uncertainty class. We investigate both decentralized detection rules, where agents collaborate to minimize the error probability of the final agent, and social learning rules, where each agent minimizes its own local minimax error probability. We then extend our results to the infinite tandem network, and derive necessary and sufficient conditions on the uncertainty classes for the minimax error probability to converge to zero when agents know their positions in the tandem. On the other hand, when agents do not know their positions in the network, we study the cases where agents collaborate to minimize the asymptotic minimax error probability, and where agents seek to minimize their worst-case minimax error probability (over all possible positions in the tandem). We show that asymptotic learning of the true hypothesis is no longer possible in these cases, and derive characterizations for the minimax error performance.

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arXiv2014

Cooperation and Storage Tradeoffs in Power-Grids with Renewable Energy Resources

One of the most important challenges in smart grid systems is the integration of renewable energy resources into its design. In this work, two different techniques to mitigate the time varying and intermittent nature of renewable energy generation are considered. The first one is the use of storage, which smooths out the fluctuations in the renewable energy generation across time. The second technique is the concept of distributed generation combined with cooperation by exchanging energy among the distributed sources. This technique averages out the variation in energy production across space. This paper analyzes the trade-off between these two techniques. The problem is formulated as a stochastic optimization problem with the objective of minimizing the time average cost of energy exchange within the grid. First, an analytical model of the optimal cost is provided by investigating the steady state of the system for some specific scenarios. Then, an algorithm to solve the cost minimization problem using the technique of Lyapunov optimization is developed and results for the performance of the algorithm are provided. These results show that in the presence of limited storage devices, the grid can benefit greatly from cooperation, whereas in the presence of large storage capacity, cooperation does not yield much benefit. Further, it is observed that most of the gains from cooperation can be obtained by exchanging energy only among a few energy harvesting sources.

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arXiv2014

Distributed Local Linear Parameter Estimation using Gaussian SPAWN

We consider the problem of estimating local sensor parameters, where the local parameters and sensor observations are related through linear stochastic models. Sensors exchange messages and cooperate with each other to estimate their own local parameters iteratively. We study the Gaussian Sum-Product Algorithm over a Wireless Network (gSPAWN) procedure, which is based on belief propagation, but uses fixed size broadcast messages at each sensor instead. Compared with the popular diffusion strategies for performing network parameter estimation, whose communication cost at each sensor increases with increasing network density, the gSPAWN algorithm allows sensors to broadcast a message whose size does not depend on the network size or density, making it more suitable for applications in wireless sensor networks. We show that the gSPAWN algorithm converges in mean and has mean-square stability under some technical sufficient conditions, and we describe an application of the gSPAWN algorithm to a network localization problem in non-line-of-sight environments. Numerical results suggest that gSPAWN converges much faster in general than the diffusion method, and has lower communication costs, with comparable root mean square errors.

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arXiv2013

Successive Interference Cancellation in Heterogeneous Cellular Networks

At present, operators address the explosive growth of mobile data demand by densification of the cellular network so as to reduce the transmitter-receiver distance and to achieve higher spectral efficiency. Due to such network densification and the intense proliferation of wireless devices, modern wireless networks are interference-limited, which motivates the use of interference mitigation and coordination techniques. In this work, we develop a statistical framework to evaluate the performance of multi-tier heterogeneous networks with successive interference cancellation (SIC) capabilities, accounting for the computational complexity of the cancellation scheme and relevant network related parameters such as random location of the access points (APs) and mobile users, and the characteristics of the wireless propagation channel. We explicitly model the consecutive events of canceling interferers and we derive the success probability to cancel the n-th strongest signal and to decode the signal of interest after n cancellations. When users are connected to the AP which provides the maximum average received signal power, the analysis indicates that the performance gains of SIC diminish quickly with n and the benefits are modest for realistic values of the signal-to-interference ratio (SIR). We extend the statistical model to include several association policies where distinct gains of SIC are expected: (i) minimum load association, (ii) maxi- mum instantaneous SIR association, and (iii) range expansion. Numerical results show the effectiveness of SIC for the considered association policies. This work deepens the understanding of SIC by defining the achievable gains for different association policies in multi-tier heterogeneous networks.

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arXiv2013

Optimal Charging of Electric Vehicles in Smart Grid: Characterization and Valley-Filling Algorithms

Electric vehicles (EVs) offer an attractive long-term solution to reduce the dependence on fossil fuel and greenhouse gas emission. However, a fleet of EVs with different EV battery charging rate constraints, that is distributed across a smart power grid network requires a coordinated charging schedule to minimize the power generation and EV charging costs. In this paper, we study a joint optimal power flow (OPF) and EV charging problem that augments the OPF problem with charging EVs over time. While the OPF problem is generally nonconvex and nonsmooth, it is shown recently that the OPF problem can be solved optimally for most practical power networks using its convex dual problem. Building on this zero duality gap result, we study a nested optimization approach to decompose the joint OPF and EV charging problem. We characterize the optimal offline EV charging schedule to be a valley-filling profile, which allows us to develop an optimal offline algorithm with computational complexity that is significantly lower than centralized interior point solvers. Furthermore, we propose a decentralized online algorithm that dynamically tracks the valley-filling profile. Our algorithms are evaluated on the IEEE 14 bus system, and the simulations show that the online algorithm performs almost near optimality ($<1%$ relative difference from the offline optimal solution) under different settings.

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arXiv2011

Enhanced Inter-Cell Interference Coordination Challenges in Heterogeneous Networks

3GPP LTE-Advanced has started a new study item to investigate Heterogeneous Network (HetNet) deployments as a cost effective way to deal with the unrelenting traffic demand. HetNets consist of a mix of macrocells, remote radio heads, and low-power nodes such as picocells, femtocells, and relays. Leveraging network topology, increasing the proximity between the access network and the end-users, has the potential to provide the next significant performance leap in wireless networks, improving spatial spectrum reuse and enhancing indoor coverage. Nevertheless, deployment of a large number of small cells overlaying the macrocells is not without new technical challenges. In this article, we present the concept of heterogeneous networks and also describe the major technical challenges associated with such network architecture. We focus in particular on the standardization activities within the 3GPP related to enhanced inter-cell interference coordination.

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arXiv2011

Cooperative and Distributed Localization for Wireless Sensor Networks in Multipath Environments

We consider the problem of sensor localization in a wireless network in a multipath environment, where time and angle of arrival information are available at each sensor. We propose a distributed algorithm based on belief propagation, which allows sensors to cooperatively self-localize with respect to one single anchor in a multihop network. The algorithm has low overhead and is scalable. Simulations show that although the network is loopy, the proposed algorithm converges, and achieves good localization accuracy.

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arXiv2009

Two-Way Relay Channels: Error Exponents and Resource Allocation

In a two-way relay network, two terminals exchange information over a shared wireless half-duplex channel with the help of a relay. Due to its fundamental and practical importance, there has been an increasing interest in this channel. However, surprisingly, there has been little work that characterizes the fundamental tradeoff between the communication reliability and transmission rate across all signal-to-noise ratios. In this paper, we consider amplify-and-forward (AF) two-way relaying due to its simplicity. We first derive the random coding error exponent for the link in each direction. From the exponent expression, the capacity and cutoff rate for each link are also deduced. We then put forth the notion of the bottleneck error exponent, which is the worst exponent decay between the two links, to give us insight into the fundamental tradeoff between the rate pair and information-exchange reliability of the two terminals. As applications of the error exponent analysis, we present two optimal resource allocations to maximize the bottleneck error exponent: i) the optimal rate allocation under a sum-rate constraint and its closed-form quasi-optimal solution that requires only knowledge of the capacity and cutoff rate of each link; and ii) the optimal power allocation under a total power constraint, which is formulated as a quasi-convex optimization problem. Numerical results verify our analysis and the effectiveness of the optimal rate and power allocations in maximizing the bottleneck error exponent.

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