NL-COMM: Enabling High-Performing Next-Generation Networks via Advanced Non-Linear Processing
Abstract
1. Introduction
- We introduce an efficient, generalized and massively parallelizable NL processing framework (NL-COMM) that applies in general to non-orthogonal signal transmissions both in the uplink and the downlink (Section 4). NL-COMM also includes the necessary radio resource management functionalities required to integrate advanced NL processing into existing networks.
- We evaluate how NL-COMM can enable the promising gains of non-orthogonal transmissions in practice (Section 5). In particular, we consider how NL-COMM can apply to both traditional and distributed cell-free MIMO scenarios, the substantial throughput and connectivity gains it provides, and how these gains can also translate to system-level power savings.
- We present both software- and hardware-based solutions for NL-COMM processing (Section 6), exploiting the intrinsic characteristics of each platform to achieve real-time performance, and demonstrating their effectiveness through over-the-air evaluations.
Related Work
2. A Generic System Model for Non-Orthogonal Signal Transmissions
2.1. Uplink
2.2. Downlink
2.3. Examples of Interference Matrices
- Spatially multiplexed MIMO systems: In an uplink spatially multiplexed MIMO system with K single-antenna user equipment (UE)s and M base station antennas, the corresponding MIMO channel matrix is .
- NOMA systems: In a code-domain NOMA system, an (orthogonal) subcarrier is loaded with the signals of multiple users, which are superimposed. Specifically, the received signal vector for an LDS-OFDM system where M orthogonal subcarriers are occupied by K users is given by
3. Transceiver Processing Challenge for Non-Orthogonal Signal Transmissions
3.1. Uplink
3.1.1. Non-Linear Joint Soft Information Processing
3.2. Downlink
4. NL-COMM: An Efficient, Massively Parallelizable Non-Linear Processing Framework
4.1. Motivation
4.2. NL-COMM PHY Processing
4.2.1. Principles
4.2.2. Uplink
4.2.3. Downlink
4.3. NL-COMM Radio Resource Management
5. Evaluations of Potential Gains and Opportunities
5.1. Enhancing Spectral Efficiency
5.2. Enhancing Energy Efficiency in MIMO Systems
5.3. Enabling Massive Connectivity
5.4. Boosting-Distributed MIMO Performance
5.4.1. Centralized Processing in Open RAN-Based Distributed MIMO Systems
5.4.2. Decentralized Processing for Distributed MIMO Systems
6. Realizing NL-COMM: Software, Hardware, and System-Level Demonstrations
6.1. Software-Based Design
6.2. Hardware-Based Design
7. Over-the-Air Demonstration Platform
8. Conclusions and Future Directions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Resource | 1PU | 2PU | 4PU | 8PU |
---|---|---|---|---|
LUT | 402.5 k | 423.2 k | 462.7 k | 544.2 k |
LUTRAM | 21.7 k | 22.7 k | 24.9 k | 29.2 k |
FF | 425.3 k | 445.8 k | 497.0 k | 593.8 k |
DSP | 2.0 k | 2.3 k | 3.1 k | 4.6 k |
BRAM + URAM | 405 | 455 | 506 | 600 |
Static Power (W) | 2.9 | 3.1 | 3.3 | 3.7 |
Dynamic Power (W) | 15.5 | 18.6 | 26.6 | 39.3 |
Total Power (W) | 18.4 | 21.7 | 29.9 | 43.0 |
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Jayawardena, C.; Katsaros, G.N.; Nikitopoulos, K. NL-COMM: Enabling High-Performing Next-Generation Networks via Advanced Non-Linear Processing. Future Internet 2025, 17, 447. https://doi.org/10.3390/fi17100447
Jayawardena C, Katsaros GN, Nikitopoulos K. NL-COMM: Enabling High-Performing Next-Generation Networks via Advanced Non-Linear Processing. Future Internet. 2025; 17(10):447. https://doi.org/10.3390/fi17100447
Chicago/Turabian StyleJayawardena, Chathura, George Ntavazlis Katsaros, and Konstantinos Nikitopoulos. 2025. "NL-COMM: Enabling High-Performing Next-Generation Networks via Advanced Non-Linear Processing" Future Internet 17, no. 10: 447. https://doi.org/10.3390/fi17100447
APA StyleJayawardena, C., Katsaros, G. N., & Nikitopoulos, K. (2025). NL-COMM: Enabling High-Performing Next-Generation Networks via Advanced Non-Linear Processing. Future Internet, 17(10), 447. https://doi.org/10.3390/fi17100447