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Register a new userA Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead
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Added by
Alessio Zappone
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.
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Physical layer security which safeguards data confidentiality based on the information-theoretic approaches has received significant research interest recently. The key idea behind physical layer security is to utilize the intrinsic randomness of the transmission channel to guarantee the security in physical layer. The evolution towards 5G wireless communications poses new challenges for physical layer security research. This paper provides a latest survey of the physical layer security research on various promising 5G technologies, including physical layer security coding, massive multiple-input multiple-output, millimeter wave communications, heterogeneous networks, non-orthogonal multiple access, full duplex technology, etc. Technical challenges which remain unresolved at the time of writing are summarized and the future trends of physical layer security in 5G and beyond are discussed.
The recent progress in the area of self-interference cancellation (SIC) design has enabled the development of full-duplex (FD) single and multiple antenna systems. In this paper, we propose a design for FD eNodeB (eNB) and user equipment (UE) for 5G networks. The use of FD operation enables simultaneous in-band uplink and downlink operation and thereby cutting down the spectrum requirement by half. FD operation requires the same subcarrier allocation to UE in both uplink and downlink. Long Term Evolution LTE) uses orthogonal frequency division multiple access (OFDMA) for downlink. To enable FD operation, we propose using single carrier frequency division multiple access SC-FDMA) for downlink along with the conventional method of using it for uplink. Taking advantage of channel reciprocity, singular value decomposition (SVD) based eamforming in the downlink allows multiple users (MU) to operate on same set of subcarriers. In uplink, frequency domain minimum mean square error (MMSE) equalizer along with successive interference cancellation with optimal ordering (SSIC-OO) algorithm is used to decouple signals of users operating in the same set of subcarriers. The work includes simulations showing efficient FD operation both at UE and eNB for downlink and uplink respectively.
Gossip algorithms for distributed computation are attractive due to their simplicity, distributed nature, and robustness in noisy and uncertain environments. However, using standard gossip algorithms can lead to a significant waste in energy by repeatedly recirculating redundant information. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is related to the slow mixing times of random walks on the communication graph. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing geographic routing combined with a simple resampling method, we demonstrate substantial gains over previously proposed gossip protocols. For regular graphs such as the ring or grid, our algorithm improves standard gossip by factors of $n$ and $sqrt{n}$ respectively. For the more challenging case of random geometric graphs, our algorithm computes the true average to accuracy $epsilon$ using $O(frac{n^{1.5}}{sqrt{log n}} log epsilon^{-1})$ radio transmissions, which yields a $sqrt{frac{n}{log n}}$ factor improvement over standard gossip algorithms. We illustrate these theoretical results with experimental comparisons between our algorithm and standard methods as applied to various classes of random fields.
We study in this paper optimal control strategy for Advanced Sleep Modes (ASM) in 5G networks. ASM correspond to different levels of sleep modes ranging from deactivation of some components of the base station for several micro-seconds to switching off of almost all of them for one second or more. ASMs are made possible in 5G networks thanks to the definition of so-called lean carrier radio access which allows for configurable signaling periodicities. We model such a system using Markov Decision Processes (MDP) and find optimal sleep policy in terms of a trade-off between saved power consumption versus additional incurred delay for user traffic which has to wait for the network components to be woken-up and serve it. Eventually, for the system not to oscillate between sleep levels, we add a switching component in the cost function and show its impact on the energy reduction versus delay trade-off.
In forthcoming years, the Internet of Things (IoT) will connect billions of smart devices generating and uploading a deluge of data to the cloud. If successfully extracted, the knowledge buried in the data can significantly improve the quality of life and foster economic growth. However, a critical bottleneck for realising the efficient IoT is the pressure it puts on the existing communication infrastructures, requiring transfer of enormous data volumes. Aiming at addressing this problem, we propose a novel architecture dubbed Condense, which integrates the IoT-communication infrastructure into data analysis. This is achieved via the generic concept of network function computation: Instead of merely transferring data from the IoT sources to the cloud, the communication infrastructure should actively participate in the data analysis by carefully designed en-route processing. We define the Condense architecture, its basic layers, and the interactions among its constituent modules. Further, from the implementation side, we describe how Condense can be integrated into the 3rd Generation Partnership Project (3GPP) Machine Type Communications (MTC) architecture, as well as the prospects of making it a practically viable technology in a short time frame, relying on Network Function Virtualization (NFV) and Software Defined Networking (SDN). Finally, from the theoretical side, we survey the relevant literature on computing atomic functions in both analog and digital domains, as well as on function decomposition over networks, highlighting challenges, insights, and future directions for exploiting these techniques within practical 3GPP MTC architecture.
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