Enhancing wireless communication systems through large intelligent surfaces: a performance analysis of LIS-assisted NOMA networks

Implementing fifth-generation (5G) mobile networks aims to establish a linked society by enabling many forms of communication, including interactions between computers, humans, and other entities. However, these emerging models have disadvantages, such as increased energy consumption and reduced delay, when establishing connections between several data-intensive heterogeneous devices with varying requirements.

To overcome these challenges, it is imperative to have cutting-edge technologies that can effectively manage high data rates, numerous connections, and minimal latency. Non-orthogonal multiple access (NOMA) has emerged as a vital technology for 5G networks because of its advantages, such as reduced latency, improved connection reliability, and remarkable energy and spectrum economy. However, wireless channels are very unpredictable and susceptible to such problems as signal loss, obstruction, and absorption, leading to inevitable instances of multipath fading. While MIMO approaches can address these problems, they do result in reduced energy efficiency, which poses a significant challenge for the development of 5G and future wireless networks. In recent times, LIS technology has become increasingly popular because of its energy and spectrally-efficient nature. It enables users to have precise control over the wireless environment according to their preferences. LIS can address these constraints by employing reflecting elements (REs), which control incoming electromagnetic waves by reflection, refraction, absorption, steering, focusing, and polarization.

The integration of Localized Information Sharing (LIS) into Non-Orthogonal Multiple Access (NOMA) systems has produced promising outcomes. This integration enables the effective implementation of NOMA systems and the ability to tailor the propagation environment to prioritize individual users. Furthermore, LIS can modify user priority based on system requirements rather than solely dependent on the unpredictable wireless propagation environment. The integration of the LIS has been observed by the research community, as it can enhance NOMA systems. 6G communications are currently in the nascent phase of development, with no established standards or specifications as of yet. Nevertheless, specialists predict that 6G will provide accelerated data speeds, increased bandwidth, reduced latency, and enhanced dependability as compared to 5G. The implementation of 6G technology would enable operation in the terahertz (THz) frequency bands, resulting in improved data rates. Additionally, it would leverage AI-driven communication to optimize network efficiency. Furthermore, 6G would explore the potential of quantum communication for establishing secure channels. Moreover, it would utilize holographic technology to provide more immersive experiences. Furthermore, 6G would focus on improving energy efficiency and facilitating multiple connections across various communication channels. To summarize, 6G communication is an upcoming wireless technology that is currently being developed with the goal of delivering superior performance in comparison to 5G. The incorporation of Local Information Sharing (LIS) into Non-Orthogonal Multiple Access (NOMA) systems and the investigation of prospective functionalities for 6G communication signify notable progress in wireless networks.

Related work

The integration of LIS with NOMA networks is a rapidly growing field of study that combines wireless communication and intelligent surface technologies. In recent years, researchers have examined many elements of NOMA networks and intelligent surface applications. This previous work has provided the foundation for the inquiry reported in this article.

Multiple studies have examined NOMA’s advantages in wireless communication systems, highlighting its ability to improve spectral efficiency and support concurrent usage by multiple users. NOMA enables the sharing of time–frequency resources across numerous users, utilizing the power domain for user multiplexing. Research in NOMA has focused on diverse aspects, including resource allocation strategies, power control mechanisms, and decoding techniques, to optimize the overall system performance^1,2. The work in³ addresses challenges in network communications due to the evolving mobile Internet and Internet of Things. It introduces a 5G-oriented NOMA technology, exploring user pairing and power allocation algorithms. Simulation results reveal that the traversal search pairing scheme exhibits slightly better throughput than grouping, and specific power allocation algorithms outperform the flower pollination algorithm in various scenarios. The paper⁴ proposes a NOMA-based cooperative cellular system with a relay, showcasing its comparable performance to conventional multiple access in terms of diversity order and sum rate through the outage and ergodic sum rate analyses. Numerical simulations highlight NOMA’s potential for increased spectral efficiency and user fairness by serving more users simultaneously. Research in⁵ demonstrates the application of NOMA in 6G networks, investigating the benefits and limitations of Successive Interference Cancellation (SIC) based on quality-of-service and channel state information. Additionally, it investigates how NOMA, particularly in large-scale interconnections, can fulfil the performance requirements of 6G networks. Unlike orthogonal multiple access (OMA), non-terrestrial NOMA networks supported by RIS exhibit greater outage resilience. The work in⁶ proposes using discrete wavelet transform (DWT) for NOMA pulse shaping instead of the traditional FFT-based method, showing that wavelet-based NOMA (WNOMA) has a lower bit error rate (BER) in additive white Gaussian noise. The study in⁷ introduces a downlink NOMA-based coordinated direct and relay system with one cell-center user and multiple cell-edge users using a decode-and-forward relay in full-duplex (FD) or half-duplex (HD) modes. It finds that FD outperforms HD at low SNR, while HD is better at high SNR, with mutual interference having a significant impact on performance. The research in⁸ investigates a UAV-enabled massive MIMO NOMA full-duplex two-way relay (TWR) system with low-resolution ADCs/DACs for multi-pair ground users, deriving expressions for sum spectral and energy efficiency (SE/EE) under imperfect conditions. Results show that increasing antenna scale and proper power scaling enhance performance, UAV height adjustment benefits SE, and the SE/EE trade-off is optimized by selecting the correct number of ADC/DAC quantization bits.

However, the use of reconfigurable intelligent surfaces (RIS) has gained significant attention because of its ability to modify and control wireless propagation conditions⁹. The work in¹⁰ offers a detailed summary of the latest research progress in RIS, highlighting its ability to enhance the performance of future wireless communication networks by adjusting to changing propagation conditions. This analysis focuses on critical issues that affect the profitability of future deployments. It includes topics such as practical hardware design, artificial intelligence techniques, system models, use cases, and strategies for improving the physical layer. These surfaces consist of several passive parts and can dynamically change reflection coefficients, which can effectively impact wireless channels^11,12. Prior research has investigated the utilization of LIS in many communication settings, such as improving coverage, signal quality, and overall system capacity in large MIMO systems and millimeter-wave communication. The study in¹³ is a comprehensive examination of the functioning, enhancement, and evaluation of reconfigurable intelligent surfaces. It delves into many optimization frameworks that aim to achieve objectives like energy efficiency, sum rate, secrecy rate, and coverage. RIS is emerging as a promising candidate for supporting 6G wireless networks¹⁴. The research in¹⁵ delves into the forefront of 6G wireless communication, highlighting innovative materials, radio-frequency architectures, and transformative communication paradigms. RISs are identified as pioneering 6G technology, offering programmable artificial structures capable of manipulating electromagnetic fields for diverse networking goals. The paper categorizes advancements in RIS hardware, unit element modeling, and signal propagation, with a focus on channel estimation for optimized RIS integration. Additionally, it explores the relevance of RIS in current wireless standards, shedding light on ongoing and future standardization efforts for RIS technology and its empowered networking approaches. Further emphasizing the potential of reconfigurable intelligent surfaces (RISs) to enhance wireless network performance, Hassouna et al.¹⁶ covers principles, performance analysis, and challenges in integrating passive components efficiently. The study compares channel estimation for different RIS types and deployment scenarios, concluding with proposed future research areas for RIS-aided wireless communication systems. To address challenges posed by internet-dependent 5G technology, Bariah et al.¹⁷ proposes implementing Internet of Things (IoT)-based 6G technology. It develops a closed-form formula that accurately determines the coverage probability for nearby and distant users in a NOMA system with RIS support. The work in¹⁸ explores the role of RISs in wireless communication, comparing RIS technology with the SISO case and evaluating performance in terms of data rate and energy efficiency. The study investigates the impact on wireless sensor networks, showcasing spectral efficiency gains with sufficiently large RIS sizes. Key open issues for maximizing RIS benefits in wireless communications and networks are discussed.

Innovatively, the research in¹⁹ proposes a reconfigurable reflective meta surface with integrated sensing capabilities, aiming to enhance wireless communication and power transfer by providing the reflective surface with prior knowledge of the propagation environment. This technology, by modifying tunable meta-atoms, can sample incident waves and detect properties such as the angle of arrival, potentially reducing the number of required sensors through tunable multiplexing. The proposed technology holds promise for applications in wireless communications, wireless power transfer, RF sensing, and intelligent sensors. Addressing the challenges of massive connections and green communication, the study in²⁰ combines RIS and NOMA, focusing on a downlink RIS-aided NOMA system. The evaluation of system performance through adequate capacity (EC) for real-time services highlights NOMA’s superiority due to reduced transmission time. In two-way communication scenarios²¹, users assisted by an RIS in Rayleigh fading channels are investigated, considering both reciprocal and non-reciprocal channels. The study in²² introduces a system for serving power-domain NOMA users by optimizing passive beamforming at RISs, demonstrating superior performance over its orthogonal counterpart. In the context of NOMA networks, the performance of imperfect and perfect SIC is investigated in²³ by exploring the IRS application. Numerical results affirm the enhanced performance of IRS-assisted NOMA networks in both ergodic rate and energy efficiency over conventional cooperative communications. The work in²⁴ actively shapes incident signals through passive beamforming to enhance wireless system performance, focusing on an IRS-assisted uplink NOMA system. The proposed NOMA-based scheme outperforms OMA, emphasizing the influence of the reflecting element count on the sum rate.

Recent attention has shifted towards simultaneously transmitting and reflecting Reconfigurable Intelligent Surface (STAR-RIS) assisted NOMA due to its high secrecy ability and near-optimal performance with low complexity²⁵. The study in²⁶ explores the rate performance of a STAR-RIS-aided NOMA system, while²⁷ characterizes the coverage region of STAR-RIS-aided two-user downlink communication systems. Furthermore, Guo et al.²⁸ investigates secrecy energy efficiency maximization in uplink NOMA systems using STAR-RISs mounted on unmanned aerial vehicles (UAVs), and²⁹ proposes joint caching and simultaneous wireless information and power transfer (SWIPT) in STAR-RIS-empowered NOMA systems. Finally, Wen et al.³⁰ examines a STAR-RIS-aided NOMA system with unbalanced users, suggesting strategies for short-range applications and specific power scenarios.

The existing literature sets the stage for our investigation, highlighting the individual merits of NOMA and LIS. Our study extends this knowledge by exploring the synergies between these technologies and uncovering the unique benefits of incorporating LIS in NOMA networks. The insights gained from this research contribute to the evolving landscape of intelligent surface-assisted communication systems, guiding future developments and innovations in this promising field.

Contributions

This research study greatly enhances wireless communication systems by examining the incorporation of LIS with NOMA networks and doing a thorough analysis of its effects on system performance. This study presents the following significant contributions:

• Our suggested comprehensive system architecture has a base station (BS) integrated with a LIS. The BS uses NOMA to serve numerous users simultaneously in a downlink communication situation. The LIS employs a variety of passive devices that may be adjusted to control the reflection coefficients, improving the signal’s quality and coverage. This unique system model establishes the basis for examining the interactions between LIS and NOMA in a real-world wireless communication setting.

• We conduct a comprehensive analysis of the proposed network’s performance that uses LIS to support NOMA. We analyze essential performance indicators such as diversity gain, likelihood of mistake, and pairwise error probability (PEP). By conducting thorough analysis and simulation experiments, we present a complete understanding of how the LIS impacts the NOMA network’s overall performance. This research provides valuable insights for scholars and practitioners in this sector.

• We do a comparative analysis by evaluating the performance of the LIS-assisted NOMA network in comparison to traditional NOMA systems that do not include LIS integration. This study compares the benefits brought by the LIS in terms of increased system capacity, expanded coverage, and improved signal quality. The findings of this comparison demonstrate that the suggested LIS-assisted NOMA network outperforms the alternatives. They contribute significant information to the ongoing discourse on intelligent surface-enhanced communication systems.

• Our research offers valuable insights into the unexplored capabilities and difficulties of LIS-assisted NOMA networks. Through the identification of areas that require improvement and potential optimizations, we provide the groundwork for future research and development in this expanding subject. Our study generates knowledge that encourages researchers to delve deeper into the intricacies of LIS-NOMA integration and its broader implications for the evolution of wireless communication systems, catalysing further exploration in this emerging field.

In summary, this work advances the current understanding of wireless communication systems by investigating the novel fusion of LIS and NOMA networks. The suggested system model, performance analysis, and comparative study add to what is already known in this area. They give useful information and will help guide future research that aims to utilize intelligent surface technologies in wireless communication fully.

The subsequent sections of this paper are structured as follows: “System model” section introduces the system model for the LIS-assisted NOMA network, presenting the associated mathematical expressions. In “Asymptotic diversity order” section, we discuss the pairwise error probability, while “Simulation analysis” section explores the asymptotic diversity order of the LIS-assisted NOMA. In Sect. 5, we substantiate the efficacy of the LIS-assisted NOMA through a detailed simulation analysis. Lastly, Sect. 6 offers the conclusion of this paper, summarizing the significant findings derived from our investigation.