208 research outputs found
Full-Duplex Enabled Mobile Edge Caching: From Distributed to Cooperative Caching
Mobile edge caching (MEC) has received much attention as a promising technique to overcome the stringent latency and data hungry requirements in future generation wireless networks. Meanwhile, full-duplex (FD) transmission can potentially double the spectral efficiency by allowing a node to receive and transmit in the same time/frequency block simultaneously. In this paper, we investigate the delivery time performance of full-duplex enabled MEC (FD-MEC) systems, in which the users are served by distributed edge nodes (ENs), which operate in FD mode and are equipped with a limited storage memory. Firstly, we analyse the FD-MEC with different levels of cooperation among the ENs and take into account a realistic model of self-interference cancellation. Secondly, we propose a framework to minimize the system delivery time of FD-MEC under both linear and optimal precoding designs. Thirdly, to deal with the non-convexity of the formulated problems, two iterative optimization algorithms are proposed based on the inner approximation method, whose convergence is analytically guaranteed. Finally, the effectiveness of the proposed designs are demonstrated via extensive numerical results. It is shown that the cooperative scheme mitigates inter-user and self interference significantly better than the distributed scheme at an expense of inter-EN cooperation. In addition, we show that minimum mean square error (MMSE)-based precoding design achieves the best performance-complexity trade-off, compared with the zero-forcing and optimal designs
Multiple-Access Relaying with Network Coding: Iterative Network/Channel Decoding with Imperfect CSI
International audienceIn this paper, we study the performance of the four-node multiple-access relay channel with binary Network Coding (NC) in various Rayleigh fading scenarios. In particular, two relay protocols, decode-and-forward (DF) and demodulate-and-forward (DMF) are considered. In the first case, channel decoding is performed at the relay before NC and forwarding. In the second case, only demodulation is performed at the relay. The contributions of the paper are as follows: (1) two joint network/channel decoding (JNCD) algorithms, which take into account possible decoding error at the relay, are developed in both DF and DMF relay protocols; (2) both perfect channel state information (CSI) and imperfect CSI at receivers are studied. In addition, we propose a practical method to forward the relays error characterization to the destination (quantization of the BER). This results in a fully practical scheme. (3) We show by simulation that the number of pilot symbols only affects the coding gain but not the diversity order, and that quantization accuracy affects both coding gain and diversity order. Moreover, when compared with the recent results using DMF protocol, our proposed DF protocol algorithm shows an improvement of 4 dB in fully interleaved Rayleigh fading channels and 0.7 dB in block Rayleigh fading channels
Optimal and low-complexity iterative joint network/channel decoding for the multiple-access relay channel
International audienceIn this paper, we investigate joint network and channel decoding algorithms for the multiple-access relay channel. We consider a realistic reference scenario with Rayleigh fading over all the wireless links, including the source-torelay channels. Our contribution is twofold: i) first, we develop the quasi-optimal joint network and channel decoder by taking into account possible errors over the source-torelay channels, and ii) second, we propose a low-complexity iterative joint network and channel decoding algorithm, which reduces the number of channel decoders with respect to state-of-the-art solutions. Our numerical results show that: i) in fully-interleaved Rayleigh fading channels, the proposed solution provides almost the same bit error probability as the quasi-optimal scheme but with a reduction in complexity of approximately the 65%, and ii) in Rayleigh block-fading channels, the proposed scheme yields almost the same bit error probability as state-of-the-art solutions but with a reduction in complexity of approximately the 30%
Joint Power Allocation and Access Point Selection for Cell-free Massive MIMO
Cell-free massive multiple-input multiple-output (CF-MIMO) is a promising technological enabler for fifth generation (5G) networks in which a large number of access points (APs) jointly serve the users. Each AP applies conjugate beamforming to precode data, which is based only on the AP's local channel state information. However, by having the nature of a (very) large number of APs, the operation of CF-MIMO can be energy-inefficient. In this paper, we investigate the energy efficiency performance of CF-MIMO by considering a practical energy consumption model which includes both the signal transmit energy as well as the static energy consumed by hardware components. In particular, a joint power allocation and AP selection design is proposed to minimize the total energy consumption subject to given quality of service (QoS) constraints. In order to deal with the combinatorial complexity of the formulated problem, we employ norm -based block-sparsity and successive convex optimization to leverage the AP selection process. Numerical results show significant energy savings obtained by the proposed design, compared to all-active APs scheme and the large-scale based AP selection
Power Optimization With BLER Constraint for Wireless Fronthauls in C-RAN
Cloud radio access network (C-RAN) is a novel architecture for future mobile networks to sustain the exponential traffic growth thanks to the exploitation of centralized processing. In C-RAN, one data processing center or baseband unit (BBU) communicates with users via distributed remote radio heads (RRHs), which are connected to the BBU via high capacity, low latency fronthaul links. In this letter, we study C-RAN with wireless fronthauls due to their flexibility in deployment and management. First, a tight upper bound of the system block error rate (BLER) is derived in closed-form expression via union bound analysis. Based on the derived bound, adaptive transmission schemes are proposed. Particularly, two practical power optimizations based on the BLER and pair-wise error probability (PEP) are proposed to minimize the consumed energy at the RRHs while satisfying the predefined quality of service (QoS) constraint. The premise of the proposed schemes originates from practical scenarios where most applications tolerate a certain QoS, e.g., a nonzero BLER. The effectiveness of the proposed schemes is demonstrated via intensive simulations
Energy-efficient Trajectory Design for UAV-enabled Wireless Communications with Latency Constraints
This paper studies a new energy-efficient unmanned
aerial vehicle (UAV)-enabled wireless communications, where the
UAV acts as a flying base station (BS) to serve the ground
users (GUs) within some predetermined latency limitations, e.g.,
requested timeout (RT). Our goal is to design the UAV trajectory
to minimize the total energy consumption while satisfying the
RT requirement from every GU, which is accomplished via two
consecutive subproblems: traveling time minimization and energy
minimization problems. Firstly, we propose two exhaustive search
and heuristic algorithms based on the traveling salesman problem
with time window (TSPTW) in order to minimize the UAV’s
traveling time without violating the GUs’ RT requirements. While
the exhaustive algorithm achieves the best performance at a high
computation cost, the heuristic algorithm achieves a trade-off
between the performance and complexity. Secondly, we minimize
the total energy consumption, for a given trajectory, via a joint
optimization of the UAV’s velocity along subsequent hops. Finally,
numerical results are presented to demonstrate the effectiveness
of our proposed algorithms. In particular, it is shown that the
proposed solutions outperform the reference in terms of both
energy consumption and outage performance
A general theory for anisotropic Kirchhoff-Love shells with embedded fibers and in-plane bending
In this work we present a generalized Kirchhoff-Love shell theory that can
capture anisotropy not only in stretching and out-of-plane bending, but also in
in-plane bending. This setup is particularly suitable for heterogeneous and
fibrous materials such as textiles, biomaterials, composites and pantographic
structures. The presented theory is a direct extension of existing
Kirchhoff-Love shell theory to incorporate the in-plane bending resistance of
fibers. It also extends existing high gradient Kirchhoff-Love shell theory for
initially straight fibers to initially curved fibers. To describe the
additional kinematics of multiple fiber families, a so-called in-plane
curvature tensor -- which is symmetric and of second order -- is proposed. The
effective stress tensor and the in-plane and out-of-plane moment tensors are
then identified from the mechanical power balance. These tensors are all second
order and symmetric for general materials. The constitutive equations for
hyperelastic materials are derived from different expressions of the mechanical
power balance. The weak form is also presented as it is required for
computational shell formulations based on rotation-free finite element
discretizations.Comment: This version updates reference list and improves text editing,
results unchange
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