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QoS-Aware Resource Allocation with Pilot-Aided Channel Estimation for Heterogeneous Wireless Networks.

Andres Ortega¹, Velio Tralli²

¹Telecommunications Engineering, Center for Studies and Sustainable Development (CEDS), Universidad Tecnológica Ecotec, Guayaquil 092301, Ecuador.

Sensors (Basel, Switzerland)

|June 24, 2022

Summary

This study introduces a QoS-aware Resource Allocation (RA) algorithm for heterogeneous networks (HetNets). The novel algorithm manages interference and improves performance by enabling users to share resource blocks, even with channel estimation errors.

Keywords:

OFDMA systems heterogeneous networks imperfect CSI pilot-aided channel estimation resource allocation

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Area of Science:

Wireless Communication Networks
Telecommunications Engineering
Signal Processing

Background:

Heterogeneous networks (HetNets) enhance capacity by offloading traffic to small cells.
Managing interference between macro and small cells is a key challenge in HetNets.
Pilot-aided channel estimation introduces errors that affect network performance.

Purpose of the Study:

To develop a Quality of Service (QoS)-aware Resource Allocation (RA) algorithm for two-tier HetNets.
To jointly address admission control (AC) and resource allocation under channel estimation errors.
To improve system performance and user fairness in HetNets.

Main Methods:

A novel QoS-aware RA algorithm is designed, incorporating pilot-aided channel estimation.
The algorithm enables simultaneous resource block sharing between macro cell users (CUs) and small cell users (SUs).
Adaptive power allocation is integrated to optimize performance and fairness.

Main Results:

The proposed algorithm achieves proportional rate constraints for all users, mitigating channel estimation error effects.
Rate dispersion is minimized, leading to maximized sum-rate in the downlink HetNet.
A performance penalty of up to 20% is observed compared to perfect channel state information (CSI).

Conclusions:

The developed RA algorithm effectively manages interference and improves resource utilization in HetNets.
The algorithm ensures fairness and proportional rates for users despite channel estimation inaccuracies.
This research provides a viable solution for enhancing HetNet performance in realistic deployment scenarios.