Performance Analysis of IRS-Assisted THz Communication Systems over α-μ Fading Channels with Pointing Errors

Area of Science:

• Wireless Communication
• Electromagnetics
• Signal Processing

Background:

• Terahertz (THz) wireless communication offers high bandwidth but faces challenges like path loss and sensitivity to misalignment.
• Intelligent Reflecting Surfaces (IRS) are emerging as a technology to enhance wireless communication by controlling the propagation environment.
• Pointing errors, especially in indoor THz scenarios, significantly impact system performance.

Purpose of the Study:

• To analyze the performance of an IRS-aided THz wireless communication system considering pointing errors.
• To derive analytical expressions for key performance metrics like ergodic capacity and outage probability.
• To investigate the impact of IRS configuration on system performance under fading conditions.

Main Methods:

• Utilizing the alpha-mu (α-μ) fading channel model, validated for THz indoor environments.
• Deriving closed-form expressions for upper-bounded ergodic capacity.
• Developing approximate expressions for outage probability, considering both IRS-reflected and direct channels.
• Validating analytical results using Monte Carlo simulations.

Main Results:

• Pointing errors introduce performance degradation in IRS-assisted THz systems.
• The performance degradation due to pointing errors can be mitigated by increasing the number of reflecting elements in the IRS.
• The α-μ fading model accurately represents THz small-scale fading statistics.

Conclusions:

• IRS technology shows promise for enhancing THz wireless communication, but careful consideration of pointing errors is crucial.
• The number of IRS reflecting elements is a critical design parameter for overcoming misalignment losses.
• The derived analytical models provide valuable tools for the performance evaluation and design of future THz IRS systems.