Efficient Multielement Ray Tracing With Site-Specific Comparisons Using Measured MIMO Channel Data

Ng, K.H.; Tameh, E.K.; Doufexi, Angela; Hunukumbure, Mythri; Nix, Andrew R

doi:10.1109/tvt.2007.895606

Cited by 57 publications

(41 citation statements)

References 44 publications

(53 reference statements)

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“…A state-of-the-art outdoor 3D ray-tracer [10] was used to model the time varying channel matrix H between the AP and each user equipment (UE) in order to replicate the time correlated nature of the received signal as the users move along the site. The ray-tracer makes use of the physical laws of radiowave propagation, such as reflection, diffraction and scattering and identifies all significant ray paths between the AP and the UE in 3D space.…”

Section: A System and Channel Modelmentioning

confidence: 99%

An Adaptive Raptor Enabled Data Carousel for File Delivery in 802.11 Multicast Networks

Bulut

Doufexi

Nix

2014

2015 IEEE Global Communications Conference (GLOBECOM)

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Section: A System and Channel Modelmentioning

confidence: 99%

An Adaptive Raptor Enabled Data Carousel for File Delivery in 802.11 Multicast Networks

Bulut

Doufexi

Nix

2014

2015 IEEE Global Communications Conference (GLOBECOM)

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“…The model uses a site-specific multi-element ray tracing model that is capable of supporting a wide range of propagation mechanisms [14]. The ray tracing scenario considers an outdoor, urban environment in central Bristol, UK, (illustrated in Figure 3) and consists of a BS located on a building top (23m above ground level) and a grid of possible MS locations (1.7m above ground).…”

Section: Performance Analysismentioning

confidence: 99%

“…For MSs with different received SNR and fading statistics, the level of fairness of different scheduling algorithms can be demonstrated statistically and the best fairness scheduling algorithm maximises the following metric proposed in [14]:…”

Section: B Performance Of Lrb-ofdma Employing Ga Pfa and Fca In A Rmentioning

confidence: 99%

Layered Random Beamforming OFDMA with Fair Scheduling Algorithms

Han

Doufexi

Armour

et al. 2008

VTC Spring 2008 - IEEE Vehicular Technology Conference

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Abstract-This paper presents performance analysis of Layered Random Beamforming (LRB) -MIMO-OFDMA employing various resource scheduling algorithms with feedback reduction in a realistic outdoor environment. LRB enables the exploitation of spatial multi-user diversity gain, spatial multiplexing capacity gain and layer spatial multi-user diversity gain, which is achieved by enabling the multiplex of data transmitted simultaneously to different destinations. Unlike a conventional beamforming system, an LRB system only requires an effective signal to interference and noise ratio (ESINR) based numerical data rate as feedback from every spatial layer of the MIMO channel and thus has potentially lower feedback requirements than a system which requires feedback of more detailed channel information. By combining the LRB technique with OFDMA, LRB-OFDMA can achieve an additional spectral multi-user diversity gain compared to the single carrier LRB system. Various scheduling algorithms are proposed for LRB-OFDMA and they show a trade-off between maintaining fairness and minimising delay. The performance of LRB-OFDMA is evaluated using some well-established statistical channel models as well as a propagation modeling tool, which represents a realistic outdoor environment.Index Terms-Layered Random Beamforming, MIMO-OFDMA, Multi-user Diversity, Scheduling Algorithm. I. INTRODUCTIONESEARCH on future generation cellular systems has focused on supporting multi-user transmission and providing higher data rates and spectral efficiency. An OFDMA system is one of the most promising PHY and multiple access candidates for future communication systems [1]. For example, the WiMAX standard (802.16) uses OFDMA as the air interface [2] and the Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) has already assumed that the downlink of the air interface would be OFDMA based [3]. Performance can be further improved by employing MIMO. Eigenbeamforming [4][5] is a capacity achieving transmission scheme that utilises singular value decomposition (SVD) and requires full channel state information (CSI) at the transmitter. However, this feedback amount increases with the product of the numbers of transmit and receive antennas.In a multi-user environment, there is likely to be at least one mobile station (MS) whose channel is near its peak at one time and/or frequency, provided different MSs experience independent fading channels. Application of a randomly generated beamforming pattern at the transmitter to achieve Opportunistic Beamforming is proposed in [6] and it can effectively exploit multi-user diversity in combination with transmit beamforming to attain the coherent beamforming capacity and only requires the feedback of signal to noise ratio (SNR) (no spatial information is required). By combining the opportunistic beamforming concept and SVD technique, [7] and [8] extend this theory to a single carrier MIMO system and develop the Random Beamforming (RB) and Layered Random Beamforming (LRB) techniques respectively. RB is ca...

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“…Methods have been proposed which could reduce the computational burden while modelling reflections, refractions, diffractions and scattering. One of the techniques proposed is image ray tracing [Ng et al, 2007].…”

Section: Experimental Characterization Of Mimo Channelmentioning

confidence: 99%

An experimental investigation into the feasibility of MIMO techniques within the HF band

Abbasi

2007

2nd European Conference on Antennas and Propagation (EuCAP 2007)

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An experimental investigation into the feasibility of MIMO techniques within the HF band Abstract MIMO research so far has primarily focussed on the VHF-SHF frequency bands with an aim to increase the data rates achieved over a limited spectrum. MIMO requires a rich scattering environment in order to create parallel spatial data pipes between antennas at the transmitter and the receiver. The HF band is also affected by the multipath effects through reflections in the different layers of the ionosphere and hence is a suitable candidate for MIMO. It was determined that antenna modelling could be used to design small, collocated antenna arrays for HF-MIMO application.This research may act as the foundation stone on which the future endeavours into the application of MIMO techniques in the HF band could be built.iii Acknowledgement It is a pleasure for me to thank the people who contributed towards this research. My gratitude goes to Professor Mike Warrington who supervised this research and was always willing to encourage and support me in addition to the invaluable input and suggestions. Dr. David Siddle as co-supervisor was always there to listen and advise, no matter how busy he was. I would also like to acknowledge Dr. Salil Gunashekar for his forthcoming support and co-operation throughout this project.I am indebted to my wife who supported me all along and showed great patience. She shielded me from many day to day worries and allowed me the time and space to concentrate on my research.

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Efficient Multielement Ray Tracing With Site-Specific Comparisons Using Measured MIMO Channel Data

Cited by 57 publications

References 44 publications

An Adaptive Raptor Enabled Data Carousel for File Delivery in 802.11 Multicast Networks

An Adaptive Raptor Enabled Data Carousel for File Delivery in 802.11 Multicast Networks

Layered Random Beamforming OFDMA with Fair Scheduling Algorithms

An experimental investigation into the feasibility of MIMO techniques within the HF band

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