Reconfigurable Intelligent Surface-Enabled millimetre Wave Communication for Beyond 5G Cellular Networks

Informations projet

RISE-MM

N° de convention de subvention: 101061011

DOI

10.3030/101061011

Projet clôturé

Date de signature de la CE 7 Juin 2022

Date de début 1 Juillet 2022

Date de fin 30 Septembre 2024

Financé au titre de

• Marie Skłodowska-Curie Actions (MSCA)

Coût total

Aucune donnée

Contribution de l’UE

€ 177 412,96

Coordonné par

FUNDACION IMDEA NETWORKS
Spain

Periodic Reporting for period 1 - RISE-MM (Reconfigurable Intelligent Surface-Enabled millimetre Wave Communication for Beyond 5G Cellular Networks)

Période du rapport: 2022-07-01 au 2024-09-30

Résumé du contexte et des objectifs généraux du projet

The 5G era has just begun, but demand for high-capacity, low-latency mobile communications is skyrocketing. Currently, 5G accounts for 10% of mobile data traffic (7 exabytes/month), and this is expected to exceed 50% by 2026 (126 exabytes/month). As applications like vehicle-to-vehicle and drone communication, augmented reality, and others emerge, data requirements will grow exponentially. Furthermore, the demand for ultra-reliable (99.999%) and low-latency (1 ms) communications poses significant challenges for traditional cellular networks.

The sub-6 GHz spectrum used for 5G provides only a short-term solution, as available bandwidth will soon be exhausted. To meet future needs, the telecom industry is exploring the extremely-high-frequency (EHF) band, particularly millimeter wave (mmWave) communication, which offers vast spectrum resources. However, mmWave signals face significant path loss, susceptibility to physical blockages, and limited transmission range, making them unsuitable for broad cellular use in their current form.
Reconfigurable intelligent surfaces (RIS) present a promising solution for enhancing mmWave communication. RISs are 2D surfaces with multiple scattering elements that reflect incoming signals by adjusting phase and amplitude, allowing for controllable, reconfigurable wireless environments. RIS-enabled mmWave (RISE-MM) systems enhance transmission range and capacity, offering a smoother integration with future 6G networks.

Key challenges include accurate channel modeling and path loss estimation for different RISE-MM settings (far/near-field, indoor/outdoor). Equally important is optimizing RIS configurations—such as size, placement, and reflecting angles—to maximize data rates, coverage, and minimize interference. Moreover, RISs can enhance wireless sensing (localization and object detection), though mmWave's sensitivity to blockages poses challenges. Initial studies on RIS-aided localization exist, but algorithms for multipath localization remain undeveloped. Moreover, real experimentation and testbed-based evaluations are needed to validate RISE-MM models and assess their practicality in 5G/6G scenarios.
This project focuses on three core objectives:

1- Channel Modeling and Estimation for RISE-MM: Revisiting path loss models for RISE-MM, accounting for RIS size, element states, and link geometry.
2- Joint Communication and Sensing (JCAS) through RISE-MM: Using machine learning (ML) and federated learning (FL) to optimize RISE-MM for joint communication and sensing.
3- System-Level Simulations and Real-Time Experiments: Leveraging simulators and real-world testbeds to validate RISE-MM models, ensuring feasibility for beyond 5G/6G deployments.

This project aims to bridge theoretical, simulation and testbed-based, and experimental gaps to advance RISE-MM as a key enabler for future mobile networks.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

The RISE-MM project was divided into three distinct phases. In the first phase, I explored various wireless network architectures and deployment scenarios, including near-field and far-field, as well as indoor and outdoor environments. This investigation provided a deep understanding of the technical requirements and system specifications for each architecture and scenario, which proved essential for the analytical modeling of RISE-MM channels in the next phase. To conclude the first phase, I identified a RISE-MM system model that will be used for analysis in the second phase of this project. The basic schematic of this system model is presented in Figure 1 and the polar representation of the system model is presented in Figure 2. In the second phase, building on the insights from the first, I examined how the channel state information (CSI) in RISE-MM networks degrades over time under different network conditions. I also analyzed the impact of the age of channel information on the network's communication, quality of service (QoS), and secrecy performances. This research was pioneering, leading to three novel contributions that laid the foundation for a new research area: "Age of Channel Information and Its Impact on Emerging Massive Wireless Networks." These contributions are briefly outlined below.

1- On the effective capacity of RIS-enabled mmWave networks with outdated CSI [R1]
This work investigates the impact of outdated CSI on the effective capacity of a RISE-MM downlink network, considering statistical QoS constraints. It provides practical insights for optimizing system parameters to balance performance with minimal complexity and cost in channel estimation, based solely on outdated channel information. The analysis derives a closed-form expression for the effective capacity that accounts for both the optimism in packet scheduling and the correlation between instantaneous and outdated CSI. This work identifies that RIS beam patterns significantly affect the correlation between outdated and instantaneous CSI, with narrower beams requiring more frequent reconfiguration to maintain capacity, raising channel estimation costs. Each beam pattern has an optimal beam training frequency that maximizes effective capacity. Selecting the appropriate beam pattern, based on user velocity and distance from the RIS, improves capacity while minimizing estimation overhead.

2- On the impact of age of channel information on secure RIS-assisted mmwave networks [R2]
This work investigates the impact of outdated channel information on the secrecy performance of a RISE-MM network. Specifically, it explores how aging channel information affects the joint optimization of transmit beamforming and RIS configuration, with the goal of improving network secrecy. In this study, I derived a closed-form expression for the cumulative noise effect caused by outdated channel information and inter-user interference. I then analyzed how this affects the received SINR at both the legitimate user's location and potential eavesdropping locations. Monte-Carlo simulations showed that the proposed system can still achieve adequate secrecy capacity even when outdated channel information is used for RIS configuration. This insight allows for tuning of system parameters to enhance secrecy performance while keeping the complexity and costs of channel estimation and frequent RIS reconfiguration to a minimum.

3- Optimizing QoS in Secure RIS-Assisted mmWave Network With Channel Aging [R3]
This work explores the impact of the age of channel information on secrecy performance when a RISE-MM network operates under statistical QoS constraints. Specifically, this work optimizes the QoS performance of a RISE-MM network given only outdated channel estimates. To this end, it proposes a technique for the joint optimization of transmit beamforming and RIS configuration, along with a closed-form solution for the optimal transmit power control policy. I investigate the impact of channel aging on the performance of these techniques. I first identify the factors influencing the aging process of a RISE-MM channel in both the near and far fields of the RIS. Subsequently, I examine the impact of channel aging on secrecy capacity and demonstrate that adequate secrecy capacity can still be achieved even when channel information is outdated, reducing the need for frequent RIS configuration. Moreover, the proposed optimal power control policy results reveal that operating in a high SNR regime does not necessarily increase the achievable effective secrecy capacity when the system operates under stricter QoS constraints. These findings allows system designers to adopt a more pragmatic system design approach that consumes less energy while maintaining the required QoS and secrecy performance.

Aside from the RISE-MM channel estimation analysis, I also performed work on waveform design for joint communication and sensing in RISE-MM networks. Specifically, I explore two waveform designs based on "Orthogonal Time Frequency Space (OTFS)" and "Unique Word Orthogonal Frequency Division Multiplexing (UW-OFDM)". Brief details are in the following.

4- A Low-Complexity Standard-Compliant PAPR Reduction Scheme for OTFS Modulation [R4]
OTFS modulation is known for its benefits in radar and communication waveform design, particularly for reliable transmission in high Doppler channels by mapping information symbols in the Delay-Doppler domain. However, the inverse-discrete Fourier Transform operation in OTFS results in a high Peak-to-Average Power Ratio (PAPR) in the transmitted frames. This work introduces a novel symbol pre-distortion algorithm to reduce PAPR, constrained by Error Vector Magnitude (EVM) limits. The method leverages the EVM tolerance used in wireless standards, avoiding the need for side-channel information. The pre-distortion for each symbol is determined by its contribution to peak values in the output. The approach is simple, flexible, and adds no complexity to symbol detection at the receiver.

5- UW-OFDM based Bi-Static Joint Communication and Sensing in 5G-NR Systems
This work explores the potential of using UW-OFDM for joint communication and sensing. In this scheme, the guard interval is replaced with a deterministic sequence, known as a UW, instead of the typical random Cyclic Prefix (CP). While the UW offers the same benefits as a CP, its deterministic nature allows it to be tailored for sensing applications, such as detecting multiple targets. This study designs a first-of-its-kind 5G-NR standard-compliant UW-OFDM framework for bi-static, multi-target sensing, ensuring that the system's communication performance remains unaffected.

References
[R1] Syed Waqas Haider Shah, S. P. Deram, and J. Widmer, “On the Effective Capacity of RIS-enabled mmWave Networks with Outdated CSI”, in Proc. of IEEE International Conference on Computer Communications (IEEE INFOCOM 2023), New York, United States, 2023.
[R2] Syed Waqas Haider Shah, M. Qaraqe, S. Althunibat, and J. Widmer, “On the Impact of Age of Channel Information on Secure RIS-enabled mmWave Networks”, in Proc of IEEE Vehicular Technology Conference (IEEE VTC- Spring 2024), Singapore, 2024.
[R3] Syed Waqas Haider Shah, M. Qaraqe, S. Althunibat, and J. Widmer, “Optimizing QoS in Secure RIS-Assisted mmWave Network With Channel Aging”, IEEE Transactions on Vehicular Technologies, 2024.
[R4] S. Sharma, Syed Waqas Haider Shah, and J. Widmer, “A Low-Complexity Standard-Compliant PAPR Reduction Scheme for OTFS Modulation”, in Proc of IEEE Vehicular Technology Conference (IEEE VTC-Spring 2024), Singapore, 2024.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

The RISE-MM project builds upon the state-of-the-art of channel estimation for RIS-enabled mmWave networks. All the state-of-the-art techniques propose estimating the perfect instantaneous RISE-MM channel without realizing its high signaling overhead and complexity and consequently its practicality in real-world wireless systems which are not only resource-constraint but also require ultra-low latency communication. To this end, the RISE-MM project, for the first time, provides a comprehensive investigation on the impact of age of channel information of RIS-enabled mmWave networks in different network conditions by incorporating all the relevant factors in the analysis. This investigation answers the key questions that arise when considering RISE-MM networks.

1- First, how frequently should the channel be estimated under different network conditions, and how will this impact the signaling overhead and overall network performance? Frequent channel estimation improves accuracy but increases overhead, affecting efficiency.
2- Second, what is the tradeoff between CSI aging and RIS configuration when dealing with outdated CSI to manage overhead? How outdated can the CSI be before it significantly impacts network performance? Essentially, how optimized should the RIS configuration be, knowing the available CSI is outdated?
3- Finally, how should system parameters be designed to ensure good performance while minimizing the complexity and cost of channel estimation?

These questions are especially critical for mmWave networks, where RIS uses narrow beams. If RIS configuration relies on outdated CSI and the user is mobile, the narrow beam might miss the user, leading to outages. Balancing these factors is key to maintaining efficient, reliable communication. I published the results of this investigation in three top-ranked IEEE conference papers and one IEEE transactions paper. A brief explanation of the results beyond the state of the art is given in the following.

1- Channel Estimation for RISE-MM and Impact of Age of Channel Information on System's Performance
The work in this direction offers practical insights into optimizing system parameters to achieve strong performance while minimizing the complexity and cost of channel estimation in a RISE-MM channel, particularly when relying on outdated channel estimates. The simulation and system-level results indicate that the reflected beam pattern from the RIS significantly influences the correlation between outdated and instantaneous CSI, as shown in Figure 3. Additionally, the findings suggest that a RIS must be reconfigured more frequently for narrower beam patterns to maintain a higher effective capacity. However, this increased reconfiguration frequency also raises the channel estimation costs. Moreover, this analysis also identified an optimal beam training frequency for different beam patterns that maximizes the average effective capacity, as shown in Figure 4. Therefore, selecting an appropriate beam pattern based on the user's velocity and distance from the RIS is essential. This approach not only enhances effective capacity but also reduces the signaling overhead associated with frequent channel estimations. Building upon these findings, I further investigate the impact of the age of channel information on the secrecy performance of the RISE-MM network. First, a comprehensive investigation on the factors that influence the channel aging process of the RISE-MM channel is done, as shown in Figure 5. Further, the system-level results reveal the proposed joint optimization of transmit beamforming and RIS configuration algorithm can achieve sufficient effective capacity even when outdated channel information is used for RIS configuration, as shown in Figure 6. It has enabled us to tune system parameters that ensure enhanced secrecy performance while minimizing the complexity and costs associated with channel estimation and frequent RIS configuration.

2- Joint Communication and Sensing
My work in this area is still in its early stages, as it's an emerging field with new ideas and technologies being proposed by leading research groups and telecom companies. I have explored different waveform designs, specifically OTFS and UW-OFDM, for integrating communication and sensing. In particular, I addressed the well-known issue of high PAPR in the OTFS scheme by introducing a novel symbol pre-distortion algorithm. This algorithm reduces PAPR by introducing distortion to each symbol before transmission, while adhering to EVM limits set by regulatory standards, ensuring compatibility with practical implementations. Notably, this approach is simple, flexible, and does not add complexity to symbol detection at the receiver. Additionally, I investigated the use of UW-OFDM for bi-static, multi-target sensing and communication. To advance this, I proposed a framework for integrating UW-OFDM into the 5G-NR standard for cellular networks. This work is still in its early phases, and I am actively addressing practical challenges to ensure smooth integration. Moving forward, I also plan to explore multi-technology and multi-band data fusion for enhanced scene construction and scene understanding in the context of integrated sensing and communication.

Effective capacity and correlation strength with MS mobility=10m/s for different beam patterns.

Age of channel information of RISE-MM link over time with user mobility in near and far fields.

A secure RIS-enabled mmWave communication network.

Exhaustive search for an optimal beam training frequency for different beam patterns.

Impact of channel correlation strength on secrecy performance for different RIS size and SNR regime.

Polar representation of the direct and RIS-assisted legitimate and wiretap links.