Joint Power Allocation and Access Point Selection for Cell-free Massive MIMO

in IEEE International Conference on Communications (2020)

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 ... [more ▼]

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 $l_{2,1}$-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. [less ▲]

Full-Duplex Enabled Mobile Edge Caching: From Distributed to Cooperative Caching

in IEEE Transactions on Wireless Communications (2020)

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 ... [more ▼]

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. [less ▲]

Energy-efficient Trajectory Design for UAV-enabled Wireless Communications with Latency Constraints

Scientific Conference (2019, November 03)

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 ... [more ▼]

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. [less ▲]

Joint User Grouping and Power Allocation for MISO Systems: Learning to Schedule

in IEEE European Signal Processing Conference 2019 (2019, September)

Learning-Based Resource Allocation: Efficient Content Delivery Enabled by Convolutional Neural Network

in IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019 (2019, July)

Machine Learning based Antenna Selection and Power Allocation in Multi-user MISO Systems

in 2019 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt) (2019, June)

Energy Efficient Design for Coded Caching Delivery Phase

in 2019 IEEE International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom) (2019)

Efficient 5G Edge Caching Over Satellite

Scientific Conference (2018, October)

The fifth generation (5G) wireless networks have to deal with the high data rate and stringent latency requirements due to the massive invasion of connected devices and data-hungry applications. Edge ... [more ▼]

The fifth generation (5G) wireless networks have to deal with the high data rate and stringent latency requirements due to the massive invasion of connected devices and data-hungry applications. Edge caching is a promising technique to overcome these challenges by prefetching the content closer to the end users at the edge node's local storage. In this paper, we analyze the performance of edge caching 5G networks with the aid of satellite communication systems. Firstly, we investigate the satellite-aided edge caching systems in two promising use cases: a) in dense urban areas, and b) in sparsely populated regions, e.g., rural areas. Secondly, we study the effectiveness of satellite systems via the proposed satellite-aided caching algorithm, which can be used in three configurations: i) mono-beam satellite, ii) multi-beam satellite, and iii) hybrid mode. Thirdly, the proposed caching algorithm is evaluated by using both empirical Zipf-distribution data and the more realistic Movielens dataset. [less ▲]

Energy Minimization for Cache-Assisted Content Delivery Networks With Wireless Backhaul

in IEEE Wireless Communications Letters (2018), 7(3), 332-335

Content caching is an efficient technique to reduce delivery latency and system congestion during peak-traffic time by bringing data closer to end users. In this letter, we investigate energy-efficiency ... [more ▼]

Content caching is an efficient technique to reduce delivery latency and system congestion during peak-traffic time by bringing data closer to end users. In this letter, we investigate energy-efficiency performance of cache-assisted content delivery networks with wireless backhaul by taking into account cache capability when designing the signal transmission. We consider multi-layer caching and the performance in cases when both base station and users are capable of storing content data in their local cache. Specifically, we analyze energy consumption in both backhaul and access links under two uncoded and coded caching strategies. Then two optimization problems are formulated to minimize total energy cost for the two caching strategies while satisfying some given quality of service constraint. We demonstrate via numerical results that the uncoded caching achieves higher energy efficiency than the coded caching in the small user cache size regime. [less ▲]

Latency Minimization for Content Delivery Networks with Wireless Edge Caching

in 2018 IEEE International Conference on Communications (ICC) (2018, May)