Intelligent Reflecting Surface-Assisted Multiple Access with User Pairing: NOMA or OMA?

Abstract: The integration of intelligent reflecting surface (IRS) to multiple access networks is a cost-effective solution for boosting spectrum/energy efficiency and enlarging network coverage/connections. However, due to the new capability of IRS in reconfiguring the wireless propagation channels, it is fundamentally unknown which multiple access scheme is superior in the IRS-assisted wireless network. In this letter, we pursue a theoretical performance comparison between non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) in the IRS-assisted downlink communication, for which the transmit power minimization problems are formulated under the discrete unit-modulus reflection constraint on each IRS element. We analyze the minimum transmit powers required by different multiple access schemes and compare them numerically, which turn out to not fully comply with the stereotyped superiority of NOMA over OMA in conventional systems without IRS. Moreover, to avoid the exponential complexity of the brute-force search for the optimal discrete IRS phase shifts, we propose a low-complexity solution to achieve near-optimal performance.

• The paper investigates the performance of NOMA versus OMA in IRS-assisted wireless networks, finding that NOMA's superiority is not always guaranteed.
• Key findings show that OMA (like TDMA) can sometimes require less transmit power than NOMA in IRS-assisted networks, challenging NOMA's typical advantages.
• A low-complexity optimization algorithm is introduced to efficiently configure IRS phase shifts and manage the computational complexity.

Intelligent Reflecting Surface-Assisted Multiple Access with User Pairing: NOMA or OMA?

The integration of intelligent reflecting surfaces (IRS) into wireless networks is introduced in this paper as an innovative advancement aimed at improving spectral efficiency, extending network coverage, and economizing on power consumption. IRS leverages reflective elements to manipulate the phases of incoming signals, accentuating the transmission quality through power enhancement and interference minimization.

This study fundamentally examines non-orthogonal multiple access (NOMA) relative to orthogonal multiple access (OMA) in IRS-assisted downlink communication architectures. The overarching question here is whether NOMA retains its advantage over OMA in this context, given IRS's unique ability to customize propagation channels—a trait absent in traditional wireless settings without IRS. The research investigates power minimization for both schemes when subjected to discrete unit-modulus constraints, accounting for the unique configurations IRS introduces.

Key Findings and Methodology

The primary findings are derived from analytic and numeric performance comparisons under optimal IRS phase-shift configurations. The results reveal a nuanced landscape where traditional expectations about NOMA's superiority are not straightforwardly applicable in IRS-enhanced environments. A significant conclusion is that the minimum transmit power required for frequency division multiple access (FDMA) always exceeds that of both time division multiple access (TDMA) and NOMA. Interestingly, when both users are proximally located to the IRS with balanced target rates, TDMA may demand less transmit power than NOMA—a counterintuitive insight, given NOMA's higher spectrum efficiency.

To navigate the exponential complexity of phase-shift optimization in IRS, the authors introduce a low-complexity optimization algorithm. This solution effectively approximates optimal performance, employing a linear approximation framework paired with alternating optimization, thus feasibly mitigating the heavy computational burden associated with brute-force search strategies.

Implications on IRS-Integrated Systems

The theoretical implications for IRS integration center on user pairing strategies in multiple access schemes. Specifically, coupling users with distinct rates or disparate proximities to the IRS can maximize NOMA's efficiency over OMA. Hence, designing IRS-aided networks must consider user and resource block allocation dynamically to unlock the full potential of IRS capabilities.

Practically, this research suggests that IRS technology should be prioritized in urban environments where network operators can judiciously deploy IRS to manipulate controlled propagation conditions. The IRS’s passive nature and flexibility in user pairing strategies further solidify its suitability in complex, high-density network ecosystems including massive machine-type communications and enhanced mobile broadband applications.

Future Directions

The implications of this study underscore several avenues for future exploration. Extending analyses to multi-user scenarios and diverse channel conditions will enrich understanding and practical application of NOMA/OMA hybrid strategies. Moreover, given the scalable nature of IRS and reflecting surfaces, further study into adaptive learning algorithms for real-time IRS configuration could prove beneficial. These explorations can cumulate into more sophisticated, dynamic wireless networks reflective of environmental cues—bolstered by IRS's inherent adaptability.

In summary, the paper elucidates several counterintuitive insights about IRS’s influence on multiple access performance, driving home the importance of context in leveraging modern wireless technologies. The proposed solutions illustrate pragmatic advancements in IRS research and chart a course for how future wireless systems might evolve around intelligent, adaptive surface technologies.