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In this paper, we study the energy-efficient resource allocation problem for device-to-device (D2D) communication underlaying cellular networks, which aims to maximize the minimum weighted energy efficiency of D2D links while guaranteeing minimum data rates for cellular links. We first characterize the optimal power allocation of the cellular links to transform the original resource allocation problem into the joint subchannel and power allocation problem for D2D links. We then propose three resource allocation algorithms with different complexity levels, namely, dual-based, branch-and-bound (BnB), and relaxation-based rounding (RBR) algorithms. While the dual-based algorithm solves the problem by using the dual decomposition method, the BnB and RBR algorithms tackle the problem by employing the relaxation approach. We establish the strong performance guarantees for the proposed algorithms through theoretical analysis. Extensive numerical studies demonstrate that the proposed algorithms achieve superior performance and significantly outperform a conventional algorithm. [ABSTRACT FROM PUBLISHER]

The increasing densification of telecommunications mobile networks raises the compelling problem of exposure to electromagnetic fields (EMF). In this paper, we address the particular concept of heterogeneous networks, where small cells (SCs) are deployed to build up a second layer to the existing macrocell network. SC deployment is shown to be particularly effective in reducing EMF exposure, in addition to capacity enhancement. Previous studies on EMF have focused on the uplink (UL) and downlink (DL) components separately, although they are strongly correlated. Relying on the definition of the exposure index (EI) from the European FP7 Lexnet project, we evaluate the impact on EMF exposure due to SC deployment. Guidelines for EMF-efficient deployment of SCs are first presented and evaluated. Then, a new enhanced intercell interference coordination (eICIC) algorithm using UL and DL metrics to optimize capacity and exposure to EMF is proposed. Static and self-optimizing dynamic implementations of the solution are considered, using a utility function related to the sojourn time of the users. Time-domain and frequency-domain self-optimized eICIC are compared in terms of EMF exposure reduction and capacity enhancement. The eICIC algorithms are combined with a self-optimized coverage range expansion function leading to further reduction of the EI. The proposed solution for optimizing both capacity and exposure to EMF is compared with a capacity-driven solution based on the DL metrics only. Simulation results illustrate the performance gains obtained for the different SC deployment scenarios. [ABSTRACT FROM PUBLISHER]

In wireless location, nonline-of-sight (NLOS) errors are a major error source. To improve positional performance, these errors should be identified and mitigated before measurements are used in position computations. A novel NLOS mitigation algorithm is proposed in this paper. Employing system redundancy, the algorithm derives from the distribution function of hyperbolic intersections, which is an intermediate mobile location. Cost functions based on the intermediate position are then created for each time-of-arrival measurement. NLOS errors are detected and mitigated via hypothesis tests performed on the cost functions. Simulation tests are presented in this paper, and the results verify the effectiveness of this NLOS-error-mitigation method. This paper also demonstrates that algorithm performance depends closely on receiver noise. Reducing receiver noise or providing the intermediate mobile location via external aiding can improve performance. [ABSTRACT FROM AUTHOR]

One of the key challenges in wireless networking is allocating the available radio resources to maximize key service delivery parameters such as the aggregate throughput and the multimedia quality of experience (QoE). We propose a novel and effective scheduling policy that allocates resource blocks, such that interference power is shifted toward capacity-saturated users, while improving the throughput of unsaturated users. The highlight of this paper is that the proposed scheme can dramatically improve the performance of cells that have a high discrepancy in its signal-to-noise ratio (SNR) distribution, which is typical in urban areas. The results show that a free-lunch (FL) solution is possible, whereby for negligible performance degradation in the saturated users, a large improvement in the nonsaturated users can be obtained. However, on average, the number of FL user pairings is low. By relaxing the degradation constraints, the non-FL (NFL) solution can yield a greater multiuser throughput gain. Motivated by a surge in mobile multimedia traffic, we further demonstrate that the proposed scheduling may have a profound impact on both energy efficiency and QoE of multimedia service delivery. [ABSTRACT FROM PUBLISHER]