Impact of Clustering in Indoor MIMO Propagation Using a Hybrid Channel Model
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Impact of Clustering in Indoor MIMO Propagation Using a Hybrid Channel Model Zhongwei Tang Microwave and Wireless Technology Research Laboratory, Information and Communication Group, Faculty of Engineering, University of Technology, Sydney, L24/B1, P.O. Box 123, Broadway NSW 2007, Australia Email: [email protected]
Ananda Sanagavarapu Mohan Microwave and Wireless Technology Research Laboratory, Information and Communication Group, Faculty of Engineering, University of Technology, Sydney, L24/B1, P.O. Box 123, Broadway NSW 2007, Australia Email: [email protected] Received 1 March 2004; Revised 7 October 2004 The clustering of propagating signals in indoor environments can influence the performance of multiple-input multiple-output (MIMO) systems that employ multiple-element antennas at the transmitter and receiver. In order to clarify the effect of clustering propagation on the performance of indoor MIMO systems, we propose a simple and efficient indoor MIMO channel model. The proposed model, which is validated with on-site measurements, combines the statistical characteristics of signal clusters with deterministic ray tracing approach. Using the proposed model, the effect of signal clusters and the presence of the line-of-sight component in indoor Ricean channels are studied. Simulation results on channel efficiency and the angular sensitivity for different antenna array topologies inside a specified indoor scenario are also provided. Our investigations confirm that the clustering of signals significantly affects the spatial correlation, and hence, the achievable indoor MIMO capacity. Keywords and phrases: angle sensitivity, channel efficiency, indoor propagation, signal clusters, MIMO, Ricean K factor, ray tracing.
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INTRODUCTION
The multiple-input multiple-output (MIMO) technique is being tipped as one of the most significant breakthroughs in wireless communications for achieving high data-rates without increasing the channel bandwidth [1, 2, 3, 4]. In view of its significance, the MIMO technique is considered for inclusion into the forthcoming IEEE 802.11n WLAN standard. MIMO systems have the ability to turn multipath propagation into a benefit for users by employing multiple antennas at both the transmitter and receiver to exploit multipath fading, in order to maximize data throughput. The underlying mathematical nature of MIMO, where the data is transmitted over a matrix rather than a vector channel, creates new and enormous opportunities beyond just diversity or array gain benefits. This has prompted new research on channel modelling, antenna design, coding schemes and signal processing, and so forth. In MIMO systems, the channel transfer matrix is a key component that includes the coupling information between the transmitter and the receiver and their interaction with the surrounding physical environment, through the spatial and angular features of RF propagation. It has been reported that
the correlation of the channel transfer matrix due to directional multipath propagation tends to decrease MIMO perfo
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