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7 - Dedicated Wireless Energy Harvesting in Cellular Networks: Performance Modeling and Analysis

from Part II - Architectures, Protocols, and Performance Analysis

Published online by Cambridge University Press:  01 December 2016

By
Hina Tabassum  and
Ekram Hossain
Edited by
Dusit Niyato ,
Ekram Hossain ,
Dong In Kim ,
Vijay Bhargava  and
Lotfollah Shafai
Hina Tabassum
Affiliation:
University of Manitoba, Winnipeg, MB, Canada
Ekram Hossain
Affiliation:
University of Manitoba, Winnipeg, MB, Canada
Dusit Niyato
Affiliation:
Nanyang Technological University, Singapore
Ekram Hossain
Affiliation:
University of Manitoba, Canada
Dong In Kim
Affiliation:
Sungkyunkwan University, Korea
Vijay Bhargava
Affiliation:
University of British Columbia, Vancouver
Lotfollah Shafai
Affiliation:
University of Manitoba, Canada
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Summary

Introduction

Energy harvesting in wireless cellular networks is a cornerstone of emerging 5G and beyond 5G (B5G) cellular networks as it aims to “cut the last wires” of the existing wireless devices [1]. In particular, energy harvesting has a significant potential to attract subscribers since it promotes mobility and connectivity anywhere and anytime, which is one of the key visions of next-generation wireless networks. In general, wireless energy harvesting can be classified according to the following two categories.

  1. • Ambient energy harvesting (EH). This refers to energy harvested from renewable energy sources (such as thermal, solar, wind, etc.) as well as energy harvested from radio signals of different frequencies in the environment that can be sensed by EH receivers (e.g., co-channel interference, TV or radio broadcasting, etc.).

  2. • Dedicated EH. This enables the intentional transmission of energy from dedicated energy sources to energy harvesting devices.

To satisfy the power demands of delay-constrained wireless applications, it is of utmost importance to ensure the availability of sufficient energy at the user terminals whenever required. This fact has motivated researchers toward the development of dedicated wireless-powered cellular networks (WPCNs) where dedicated energy sources or hybrid access points (HAPs) take care of both energy transfer and information transmission to and from the subscribers.

In this chapter, we focus on dedicated EH techniques. We first highlight the associated challenges. Next, we theoretically characterize and comparatively analyze a number of different network architectures for centralized and distributed dedicated wireless EH. Numerical results are provided to validate the analytical results.

Major Challenges in Dedicated Wireless Energy Harvesting

In this section, we will discuss a number of major challenges related to dedicated wireless energy harvesting (WEH) from the perspective of network architecture and modeling and resource allocation.

Network Architectures for Wireless Energy Harvesting

Different network architectures have been studied for WEH. However, most of the studies have been limited to a two- or three-node network model, a central base station (BS) that takes care of both the wireless information transmission and energy transfer, and follows a specific configuration of energy harvesting; i.e., a user harvests energy from a centralized half-duplex BS or full-duplex BS or through randomly deployed power beacons (PBs), etc.

Type
Chapter
Information
Wireless-Powered Communication Networks
Architectures, Protocols, and Applications
 , pp. 246 - 264
Publisher: Cambridge University Press
Print publication year: 2016

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References

[1] E., Hossain, M., Rasti, H., Tabassum, and A., Abdelnasser, “Evolution toward 5G multitier cellular wireless networks: An interference management perspective,” IEEE Wireless Communications, vol. 21, no. 3, pp. 118–127, June 2014.Google Scholar
[2] K. M., Thilina, H., Tabassum, E., Hossain, and D. I., Kim, “Medium access control design for full duplex wireless systems: Challenges and approaches,” IEEE Communications Magazine, vol. 53, no. 5, pp. 112–120, May 2015.Google Scholar
[3] H., Ju and R., Zhang, “Throughput maximization for wireless powered communication networks,” IEEE Transactions on Wireless Communications, vol. 13, no. 1, pp. 418–428, January 2014.Google Scholar
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[7] H., Tabassum, E., Hossain, M., Hossain, and D., Kim, “On the spectral efficiency of multiuser scheduling in RF-powered uplink cellular networks,” IEEE Transactions on Wireless Communications, vol. 14, no. 7, pp. 3586–3600, July 2015.Google Scholar
[8] K., Huang and V. K., Lau, “Enabling wireless power transfer in cellular networks: Architecture, modeling and deployment,” IEEE Transactions on Wireless Communications, vol. 13, no. 2, pp. 902–912, February 2014.Google Scholar
[9] S., Gradshteyn and I. M., Ryzhik, Table of Integrals, Series, and Products, 6th edn., New York : Academic Press, 2000.
[10] H., Tabassum, F., Yilmaz, Z., Dawy, and M.-S., Alouini, “A statistical model of uplink intercell interference with slow and fast power control mechanisms,” IEEE Transactions on Communications, vol. 12, no. 1, pp. 206–217, September 2013.Google Scholar
[11] Q. T., Zhang, “Outage probability of cellular mobile radio in the presence of multiple Nakagami interferers with arbitrary fading parameters,” IEEE Transactions on Vehicular Technology, vol. 44, no. 3, pp. 364–372, May 1996.Google Scholar
[12] K. A., Hamdi,“A useful lemma for capacity analysis of fading interference channels,” IEEE Transactions on Communications, vol. 58, no. 2, pp. 411–416, February 2010.Google Scholar

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