Abstract

5G era opens a new horizon toward communication with new features and capabilities. The new mobile generation comes up with a multi-gigabit per second data rate along with its huge available bandwidths provided by millimeter-wave frequency bands. Dispensing a fully connected world throughout low latency is the supreme aim for 5G networks. However, attaining high-speed, reliable communication is challenging in the new generation, especially in scenarios with numerous obstacles such as the urban one. As the frequency rises, the signal's penetration power declines, which can mislead TCP in adjusting the sending rate because TCP cannot distinguish that a packet drop in a network is due to congestion or other shortcomings of the network such as blockage or random packet drops. This paper proposes a new TCP based on Fuzzy logic, which strives to prevent performance reduction in urban deployments. The Fuzzy rules are implemented in the congestion avoidance phase of the new protocol to adjust the sending rate intelligently and prevent blockage impacts. The ultimate aim of the protocol is to control the sending rate based on the current situation of the network so it can attain the highest possible performance. Moreover, it tries to reach its goal through low latency and keep the average sending rate as small as possible to restrain the buffer exhaustion. The extensive conducted simulations showed that the newly proposed protocol could attain higher performance compared to BBR, HighSpeed, Cubic, and NewReno in terms of throughput, RTT, and sending rate adjustment in the urban scenario.

Highlights

  • By appearing new services and high-quality videos, exploiting high frequencies in 5G (Fifth Generation) is inevitable

  • Millimeter-wave frequency bands are going to be deployed in the new mobile generation to provide high bandwidth for the wireless channels in order to fulfill the demand for large data rates [1], [2]

  • These issues incorporate: (i) a lossy environment that can create numerous random packet losses, which leads to a high value for BER (Bit Error Rate). (ii) Being susceptible to obstacles, which creates NLoS states and makes it difficult to have stable channels for communication. (iii) Decreased throughput and increased RTT in NLoS states. (iv) Difficulties in sending rate adjustment, which leads to cwnd fluctuations. (v) Most TCPs cannot distinguish the drops caused by blockage and congestion and decrease or increase their sending rate without having a clue from the network’s status, which can lead to the underutilization of the resources, exhausting the buffers, or creating bufferbloating problem. The latter issue can be alleviated by deploying some techniques of AQM (Active Queue Management) such as CoDel [43] or FqCoDel [44]. They are not sufficient and need some modification to be deployed in 5G mmWave networks [1]

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Summary

INTRODUCTION

By appearing new services and high-quality videos, exploiting high frequencies in 5G (Fifth Generation) is inevitable. Millimeter-wave (mmWave) frequency bands are going to be deployed in the new mobile generation to provide high bandwidth for the wireless channels in order to fulfill the demand for large data rates [1], [2]. Several reasons can make the blockage effect or NLoS states more intense or relieve its negative impacts Parameters such as the number of obstacles, the topology's layout, or the distance between a UE and a gNB can play a vital role in the ultimate performance. The newly proposed protocol's main goal should be utilizing the vast available resources in 5G mmWave networks This protocol can give up being fair to some levels to use the new generation's full potential. The rest of the paper is organized as follows: section two presents the related work, section three talks about the Fuzzy logic, section four explains the newly proposed protocol, section five incorporates methodology and the simulation parameters, section six describes the simulation scenarios and the results, and section seven concludes the paper

Related work
Fuzzy Logic
FB-TCP
Convergence Phase
Divergence Phase
Methodology and the simulation parameters
GHz outage threshold
Simulation scenarios and the results
Scenario one
Scenario two
Scenario three
Findings
CONCLUSION
Full Text
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