Number of multipath clusters in indoor MIMO propagation environments

Czink, Nicolai; Herdin, M.; Ozcelik, H.; Bonek, E.

doi:10.1049/el:20046570

Cited by 40 publications

(12 citation statements)

References 6 publications

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“…However, these approaches did not incorporate the spatiotemporal correlation with parameters conditioned on the spatial domain in indoor corridor environments. Other studies on millimeter wave channel characterization can be found in [14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Statistical Channel Model for Indoor Corridor at 14 GHz, 18 GHz, and 22 GHz Bands

Oyie

Afullo

2018

Wireless Communications and Mobile Computing

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Several techniques have been proposed to overcome challenges of meeting demands for higher data rates in wireless communication. Space-time diversity method is proposed to exploit spatiotemporal nature of the channel; hence, a comprehensive knowledge of the spatiotemporal properties of a channel is required. In this paper, a measurement-based channel model that considers both delay and angular domains of an indoor corridor channel for 14 GHz, 18 GHz, and 22 GHz is proposed. A nonparametric Gaussian kernel density estimation method is applied for cluster identification for the three frequency bands. This work proposes a spatiotemporal model that conditions the model parameters on the azimuthal spatial domain. The clusters are modeled on the complete azimuth plane and a Gaussian estimation distribution is fitted onto the empirical data plot. Both clusters and multipath components are modeled and results are compared with Saleh-Valenzuela model parameter values. The results show that both clusters and multipath components can be estimated by probability density functions that follow Gaussian and Laplacian fits on the spatial domain for indoor corridor environment, respectively.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal Statistical Channel Model for Indoor Corridor at 14 GHz, 18 GHz, and 22 GHz Bands

Oyie

Afullo

2018

Wireless Communications and Mobile Computing

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“…The multipath contributing to flat fading may be spread over angles ranging from very large (e.g., within rooms) to very narrow (e.g., within long hallways). While the angle spread is often very large, it also tends to be "lumpy," being concentrated in elevation near the azimuthal plane, and within the azimuthal plane mostly in the form of discrete clusters (e.g., 4-10 such clusters at 5.2 GHz [2]) often associated with line-of-sight and specular reflection mechanisms. Diffraction contributes to blur the distinction between these clusters and to illuminate areas not accessible by line-of-sight and reflection mechanisms.…”

Section: Characteristics Of Indoor Propagationmentioning

confidence: 99%

“…This effect has been identified in some field tests (e.g., [31]) but has probably been inadvertently suppressed in many others due to the common practice of normalizing capacity statistics to a standard SNR. 2 The problem of how to make informed choices between (1) maintaining full rank by using many access points with small coverage areas, and (2) allowing some degree of rank collapse and compensating with increased SNR, is an interesting one worthy of further investigation.…”

Section: Site Planning Considerationsmentioning

confidence: 99%

“…Thus, achieving a k-fold capacity increase via MIMO requires: (1) a propagation channel capable of supporting at least k independent subchannels, and (2) arrays of at least k elements each which can "access" these subchannels with useable SNR. In practice, either (1) or (2) can limit the capacity of a MIMO channel. In this paper, we refer to the number of subchannels available with "useable" SNR as the effective rank k e of the MIMO channel, with k e ≤ k. This a useful concept since many MIMO channels in actual practice have full rank (i.e., k = min{N T , N R }) but with only k e subchannels having SNR sufficiently large to contribute significantly to the MIMO channel capacity.…”

Section: Introductionmentioning

confidence: 99%

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Antenna design and site planning considerations for MIMO

Ellingson

VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005.

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Abstract-The capacity and reliability of multiple-input multiple-output (MIMO) wireless communications systems may be sensitive to the design of the antenna arrays employed at the transmitter and receiver, as well as to the nature of the propagation between the arrays. This paper discusses the emerging methodology of array design for indoor MIMO systems used to implement wireless local area networks, and discusses some aspects of site planning which are likely to influence design choices. Some guidelines are described for choosing the number, type, and polarization of elements; element spacing and geometry; and location and orientation of arrays within rooms and hallways.

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“…Previous indoor directional measurements showed that physical paths were clustered around the receive directions and each cluster corresponded to a major path to the receiver. Using the Bartlett and SAGE estimates overlaid, Czink et al found a mean number of 7.6 clusters in a cluttered office environment [CHO++04]. Using a spatial filter on SAGE estimates, 4 to 5 clusters were obtained in [YLC++04].…”

Section: Indoor Geolocation Using Aoa-based Techniquesmentioning

confidence: 99%

Space-time channel modeling for emerging wireless techniques : a system-dependent approach

Chen¹

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List of abbreviations iv List of figures xv List of tables xxii 2.2.2 Model classification 21 2.2.3 Physically based channel models 22 viii ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library 2.2.3.1 Deterministic ray tracing models 22 2.2.3.2 Geometric channel models 24 2.2.3.3 Other stochastic ray tracing models 29 2.2.4 Non-physically based channel models 30 2.3 System-independent and system-dependent channel modeling viewpoints 32 2.3.1 General remarks 32 2.3.2 Influence of system-dependency of multipath channels on some of the emerging wireless systems 35 2.3.2.1 Degrees-of-freedom and diversity of MIMO channels 35 2.3.2.2 UWB source localization 2.4 Conclusions 3. A unified analysis for geometric channel modeling methods 40 3.1 Introduction 3.2 The semi-geometrically based statistical model 3.2.1 General remarks 3.2.2 Model description 3.2.3 The underlying connection between the spatial pattern of scatterers and actual wave propagation process 3.3 Revisiting some mostly used geometric channel models 3.3.1 Macrocellular environments 3.3.2 Microcellular or picocellular environments 3.4 Further remarks-geometric model in a discrete Manhattan world ix ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library 3.4.1 Background 60 3.4.2 Model descriptions 60 3.5 Conclusions 62 4. Parabolic distribution of scatterers in street-dominated environments 64 4.1 Introduction 64 4.2 Parabolic scattering cluster for longer-delayed waves in streetdominated environments 65 4.2.1 General remarks 65 4.2.2 PAS, angular constriction, and variance of received power in the azimuth domain at the MS 69 4.2.3 Doppler spectrum 72 4.3 Numerical results and comparisons with measurements 72 4.4 Conclusions 77 5. Effect of antenna directivity on angular power distribution at the mobile in urban macrocellular environments 81 5.1 Introduction 81 5.2 Modeling the antenna power gain pattern and distribution of geometry dependent parameter 81 5.3 The SGBS macrocell model inclusion of antenna pattern (SGBSM-AP) 84 5.3.1 General remarks 84 x

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Number of multipath clusters in indoor MIMO propagation environments

Cited by 40 publications

References 6 publications

Spatiotemporal Statistical Channel Model for Indoor Corridor at 14 GHz, 18 GHz, and 22 GHz Bands

Spatiotemporal Statistical Channel Model for Indoor Corridor at 14 GHz, 18 GHz, and 22 GHz Bands

Antenna design and site planning considerations for MIMO

Space-time channel modeling for emerging wireless techniques : a system-dependent approach

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