Paper Info
Title
Doubling Spectral Efficiency Independent Of Cell Sizes In 5g Using Hybrid Ibfd Cellular Network
Abstract
In Band Full Duplex (IBFD) is an emerging radio technology that can double Spectral Efficiency (SE), one of the key enhancement item for 5G. Due to complex processing and hardware required to realize IBFD capability, it is generally not recommended for User Equipments (UEs), while the Base Stations (BSs) can accommodate these changes. This results in Hybrid IBFD Cellular Network (HICN) that restricts IBFD capability strictly to BS and continues with legacy Half Duplex (HD) UEs. Due to this IBFD capability mismatch, frequency allocation is a challenging task in HICN and, to the best of our knowledge, a generic allocation algorithm to maximize sum-SE of a cell and work across different cell sizes is not reported yet in literature. In this paper, we propose the frequency allocation algorithm for HICN that maximizes sum-SE of a cell and shown to work independent of cell size. An adaptive and robust UE grouping algorithm is introduced that, with the knowledge of location information of UEs, shares frequencies among UEs based on their distance separation. To characterize the performance of the proposed algorithm, we have used frequency reuse efficiency (eta) that signifies the amount of frequency reuse and sum-SE for the accumulated SE achieved by all UEs in UL and DL. We have obtained closed-form analytical expression for eta as well as bounds on number of frequencies required. Simulation results reveal that the frequency reuse is doubled with increase in number of UEs, leading to doubling sum-SE for Macro, Micro and Pico BS classes.
Year
DOI
Venue
2020
10.1109/WCNCW48565.2020.9124895
2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE WORKSHOPS (WCNCW)
Keywords
DocType
ISSN
In Band Full Duplex (IBFD), UE Grouping, Frequency Reuse, Sum Spectral Efficiency Enhancement, 5G
Conference
2167-8189
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Parthiban Annamalai100.68
Jyotsna Bapat285.67
Debabrata Das36123.61