Wireless Channel and Interference

Kihero, Abuu B.; Tusha, Armed; Arslan, Hüseyin

doi:10.1002/9781119764441.ch10

Cited by 10 publications

(3 citation statements)

References 24 publications

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“…Wireless channel varies depending on the environmental conditions. For example, different path loss measurements are expected while the propagation environment is changing 21 . Moreover, environmental conditions have important effects on multipath fading, including delay spread and Doppler spread 22 …”

Section: Methodsmentioning

confidence: 99%

“…For example, different path loss measurements are expected while the propagation environment is changing. 21 Moreover, environmental conditions have important effects on multipath fading, including delay spread and Doppler spread. 22 For the first two features given in Table 1, residential area planning (e.g., urban and rural areas) and geographic characteristic of a region have effects on the wireless channel from the aspect of multipath environment level.…”

Section: Synthetic Data Generationmentioning

confidence: 99%

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Environment‐aware intelligent numerology control approach for 5G and beyond systems

Sazak,

Yazar

2024

Int J Communication

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Summary5G and beyond (5GB) systems show a flexible characteristic to meet different user communications requirements in parallel. Multi‐numerology waveform design is an important part of this human centric characteristic, however, it is necessary to make multi‐numerology planning. In this paper, the integrated sensing and communications (ISAC) concept is used with machine learning (ML) techniques to develop an intelligent numerology control mechanism for 5GB. Thanks to the ISAC capabilities, an environment‐aware system is designed, and several useful sensing information (USI) that affect the wireless channel characteristic is utilized. It is assumed that the USI is obtained through 5GB smart city networks. At that point, synthetic data generation is performed to form a new dataset with USI‐based features. Additionally, a novel feature control algorithm is proposed in the paper. Lastly, simulation results are presented for different type of ML models including several ensemble methods.

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Section: Methodsmentioning

confidence: 99%

Section: Synthetic Data Generationmentioning

confidence: 99%

Environment‐aware intelligent numerology control approach for 5G and beyond systems

Sazak,

Yazar

2024

Int J Communication

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“…Also, the assumption of white Gaussian noise greatly simplifies the performance analysis of DOA estimation. Generally, the reason for the presence of colored (correlated) noise is interference between channels, random radiation from distributed sources, echoes, unwanted interference, etc [259]. Prominent examples of this noise occur in sonar (where there is ocean noise due to marine life, waves or ships) and in radar (where the background noise consists of ground clutter, sea clutter and scattering interference) [260].…”

Section: H Estimation Of Parameters In the Presence Of Types Of Noisementioning

confidence: 99%

A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario

Molaei,

Zakeri,

Andargoli

et al. 2024

IEEE Access

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Direction-of-arrival (DOA) estimation plays a crucial role in array signal processing across various domains, including radar, sonar, wireless communications, and seismic exploration. However, traditional DOA techniques often assume either far-field (FF) or near-field (NF) propagation, limiting their applicability in scenarios involving mixed-field sources. DOA estimation and localization in scenarios involving mixed NF and FF sources is a complex and dynamic field that has garnered significant research attention in recent years. This multifaceted and evolving area holds promise for addressing challenges in radar, wireless communications, and acoustic sensing applications. This review paper provides a comprehensive overview of the methodologies, techniques, and advancements in this domain. We categorize existing methodologies, discussing their advantages and limitations. Furthermore, we delve into the mathematical modeling of mixed-field sources and essential signal processing techniques for parameter estimation. Special attention is given to technical issues such as aperture loss, computational complexity, and hardware considerations. The paper discusses the various sources of noise in the mentioned scenario and highlights the importance of modeling noise accurately for effective estimation. It also explores different scenarios and assumptions considered in the literature, ranging from non-Gaussian and nonstationary noise environments to scenarios involving multipath propagation and unknown mutual coupling effects. A detailed examination of the statistical approaches used in DOA estimation and localization reveals a diverse range of methods, including higher-order statistics and second-order statistics, each with its own advantages and applications. A comparative evaluation of various approaches highlights their performance in terms of estimation accuracy, resolution, aperture loss and computational efficiency. This provides insights into the trade-offs involved in choosing between different approaches. The review also identifies promising future research directions, such as the exploration of advanced signal processing techniques like compressive sensing and deep learning, exact NF modeling, estimation based on one-bit measurements, the integration of polarization diversity, employing metasurface antennas, tracking parameters, and the utilization of full-wave or experimental data for a more realistic representation of the challenges. By reviewing advances in methodologies and techniques, as well as outlining future research directions aimed at addressing the complexities of mixed-field scenarios, this paper paves the way for the development of more robust and reliable localization systems capable of handling real-world complexities.

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