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

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.