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Peng M.,Beijing University of Posts and Telecommunications | Wang C.,Inter Digital Communications | Lau V.,Hong Kong University of Science and Technology | Poor H.V.,Princeton University
IEEE Wireless Communications | Year: 2015

As a promising paradigm for fifth generation wireless communication systems, cloud radio access networks (C-RANs) have been shown to reduce both capital and operating expenditures, as well as to provide high spectral efficiency (SE) and energy efficiency (EE). The fronthaul in such networks, defined as the transmission link between the baseband unit and the remote radio head, requires a high capacity, but is often constrained. This article comprehensively surveys recent advances in fronthaul-constrained CRANs, including system architectures and key techniques. Particularly, major issues relating to the impact of the constrained fronthaul on SE/EE and quality of service for users, including compression and quantization, large-scale coordinated processing and clustering, and resource allocation optimization, are discussed together with corresponding potential solutions. Open issues in terms of software-defined networking, network function virtualization, and partial centralization are also identified. © 2002-2012 IEEE. Source


Peng M.,Beijing University of Posts and Telecommunications | Li Y.,Beijing University of Posts and Telecommunications | Quek T.Q.S.,Singapore University of Technology and Design | Quek T.Q.S.,Institute for Infocomm Research | Wang C.,Inter Digital Communications
IEEE Transactions on Wireless Communications | Year: 2014

Using Device-to-device (D2D) communications in a cellular network is an economical and effective approach to increase the transmission data rate and extend the coverage. Nevertheless, the D2D underlaid cellular network is challenging due to the presence of inter-tier and intra-tier interferences. With necessarily lower antenna heights in D2D communication links, the fading channels are likely to contain strong line-of-sight components, which are different from the Rayleigh fading distribution in conventional two-tier heterogeneous networks. In this paper, we derive the success probability, spatial average rate, and area spectral efficiency performances for both cellular users and D2D users by taking into account the different channel propagations that they experience. Specifically, we employ stochastic geometry as an analysis framework to derive closed-form expressions for above performance metrics. Furthermore, to reduce cross-tier interferences and improve system performances, we propose a centralized opportunistic access control scheme as well as a mode selection mechanism. According to the analysis and simulations, we obtain interesting tradeoffs that depend on the effect of the channel propagation parameter, user node density, and the spectrum occupation ratio on the different performance metrics. This work highlights the importance of incorporating the suitable channel propagation model into the system design and analysis to obtain the realistic results and conclusions. © 2002-2012 IEEE. Source


Cheng J.,Huazhong University of Science and Technology | Cheng J.,University of Prince Edward Island | Ye Q.,University of Prince Edward Island | Jiang H.,Huazhong University of Science and Technology | And 2 more authors.
IEEE Transactions on Wireless Communications | Year: 2013

Data gathering in sensor networks is required to be efficient, adaptable and robust. Recently, compressive sensing (CS) based data gathering shows promise in meeting these requirements. Existing CS-based data gathering solutions require that a transform that best sparsifies the sensor readings should be used in order to reduce the amount of data traffic in the network as much as possible. As a result, it is very likely that different transforms have to be determined for varied sensor networks, which seriously affects the adaptability of CS-based schemes. In addition, the existing schemes result in significant errors when the sampling rate of sensor data is low (equivalent to the case of high packet loss rate) because CS inherently requires that the number of measurements should exceed a certain threshold. This paper presents STCDG, an efficient data gathering scheme based on matrix completion. STCDG takes advantage of the low-rank feature instead of sparsity, thereby avoiding the problem of having to be customized for specific sensor networks. Besides, we exploit the presence of the short-term stability feature in sensor data, which further narrows down the set of feasible readings and reduces the recovery errors significantly. Furthermore, STCDG avoids the optimization problem involving empty columns by first removing the empty columns and only recovering the non-empty columns, then filling the empty columns using an optimization technique based on temporal stability. Our experimental results indicate that STCDG outperforms the state-of-the-art data gathering algorithms in terms of recovery error, power consumption, lifespan, and network capacity. © 2013 IEEE. Source


Xie X.,Beijing University of Posts and Telecommunications | Peng M.,Beijing University of Posts and Telecommunications | Zhao Z.,Beijing University of Posts and Telecommunications | Wang C.,Inter Digital Communications
2013 International Conference on Wireless Communications and Signal Processing, WCSP 2013 | Year: 2013

In this paper, the channel estimation problem for two-way relay networks with imperfect synchronization is considered where training sequences sent from the two sources can not arrive at relay simultaneously. To analyze its performance, the Crámer-Rao bound of composite channel coefficients are first derived, then the optimal power allocation is investigated aiming at minimizing the corresponding CRBs. Focusing on declining the bit error probability of signal detection at receiver, an iterative estimation algorithm is proposed based on the optimal linear estimator. Simulations are conducted to demonstrate the effectiveness of the proposed estimation algorithm. © 2013 IEEE. Source


Liu W.,Huazhong University of Science and Technology | Liu W.,Hubei University of Economics | Jiang H.,Huazhong University of Science and Technology | Bai X.,Huazhong University of Science and Technology | And 3 more authors.
Proceedings - International Conference on Distributed Computing Systems | Year: 2012

We study the problem of skeleton extraction for large-scale sensor networks using only connectivity information. Existing solutions for this problem heavily depend on an algorithm that can accurately detect network boundaries. This dependence may seriously affect the effectiveness of skeleton extraction. For example, in low density networks, boundary detection algorithms normally do not work well, potentially leading to an incorrect skeleton being generated. This paper proposes a novel approach, named DIST, to skeleton extraction from incomplete boundaries using the idea of distance transform, a concept in the computer graphics area. The main contribution is a distributed and low-cost algorithm that produces accurate network skeletons without requiring that the boundaries be complete or tight. The algorithm first establishes the network's distance transform - the hop distance of each node to the network's boundaries. Based on this, some critical skeleton nodes are identified. Next, a set of skeleton arcs are generated by controlled flooding; connecting these skeleton arcs then gives us a coarse skeleton. The algorithm finally refines the coarse skeleton by building shortest path trees, followed by a prune phase. The obtained skeletons are robust to boundary noise and shape variations. © 2012 IEEE. Source

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