paper-with-me

홈 › Papers

Computational Complexity-Constrained Spectral Efficiency Analysis for 6G Waveforms

2024-07-08 · Saulo Queiroz, João P. Vilela, Benjamin Koon Kei Ng, Chan-Tong Lam, Edmundo Monteiro

In this work, we present a tutorial on how to account for the computational time complexity overhead of signal processing in the spectral efficiency (SE) analysis of wireless waveforms. Our methodology is particularly relevant in scenarios where achieving higher SE entails a penalty in complexity, a common trade-off present in 6G candidate waveforms. We consider that SE derives from the data rate, which is impacted by time-dependent overheads. Thus, neglecting the computational complexity overhead in the SE analysis grants an unfair advantage to more computationally complex waveforms, as they require larger computational resources to meet a signal processing runtime below the symbol period. We demonstrate our points with two case studies. In the first, we refer to IEEE 802.11a-compliant baseband processors from the literature to show that their runtime significantly impacts the SE perceived by upper layers. In the second case study, we show that waveforms considered less efficient in terms of SE can outperform their more computationally expensive counterparts if provided with equivalent high-performance computational resources. Based on these cases, we believe our tutorial can address the comparative SE analysis of waveforms that operate under different computational resource constraints.

📄 PDF Abstract BibTeX arXiv:2407.05805

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

GMSR:Gradient-Guided Mamba for Spectral Reconstruction from RGB Images

2024-05-13 · Xinying Wang, Zhixiong Huang, Sifan Zhang, Jiawen Zhu 외

Mainstream approaches to spectral reconstruction (SR) primarily focus on designing Convolution- and Transformer-based architectures. However, CNN methods often face challenges in handling long-range dependencies, whereas…

Computational EfficiencyMambaSpectral Reconstruction

Spectral Efficiency vs Complexity in Downlink Algorithms for Reconfigurable Intelligent Surfaces

2020-11-10 · Pooja Nuti, Brian L. Evans

Reconfigurable Intelligent Surfaces (RIS) are an emerging technology that can be used to reconfigure the propagation environment to improve cellular communication link rates. RIS, which are thin metasurfaces composed of …

Hyperspectral Images Efficient Spatial and Spectral non-Linear Model with Bidirectional Feature Learning

2024-11-29 · Judy X Yang, Jing Wang, Zekun Long, Chenhong Sui 외

Classifying hyperspectral images (HSIs) is a complex task in remote sensing due to the high-dimensional nature and volume of data involved. To address these challenges, we propose the Spectral-Spatial non-Linear Model, a…

ClassificationComputational Efficiency

SDTN and TRN: Adaptive Spectral-Spatial Feature Extraction for Hyperspectral Image Classification

2025-07-13 · Fuyin Ye, Erwen Yao, Jianyong Chen, Fengmei He 외 arxiv

Hyperspectral image classification plays a pivotal role in precision agriculture, providing accurate insights into crop health monitoring, disease detection, and soil analysis. However, traditional methods struggle with …

Hyperspectral Image Classification

NOMA BASED SPATIAL MODULATION

2017-03-27 · journal 2017 3 · XUDONG ZHU, Zhaocheng Wang, JIANFEI CAO

Spatial modulation (SM) has emerged as a low-complexity and energy-efficient multiple-input multiple-output transmission technique, where the information bits are not only transmitted by amplitude phase modulation but …

TAG