7 research outputs found

    Hardware implementation of multiple-input multiple-output transceiver for wireless communication

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    This dissertation proposes an efficient hardware implementation scheme for iterative multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) transceiver. The transmitter incorporates linear precoder designed with instantaneous channel state information (CSI). The receiver implements MMSE-IC (minimum mean square error interference cancelation) detector, channel estimator, low-density parity-check (LDPC) decoder and other supporting modules. The proposed implementation uses QR decomposition (QRD) of complex-valued matrices with four co-ordinate rotation digital computer (CORDIC) cores and back substitution to achieve the best tradeoff between resource and throughput. The MIMO system is used in field test and the results indicate that the instantaneous CSI varies very fast in practices and the performance of linear precoder designed with instantaneous CSI is limited. Instead, statistic CSI had to be used. This dissertation also proposes a higher-rank principle Kronecker model (PKM). That exploits the statistic CSI to simulate the fading channels. The PKM is constructed by decomposing the channel correlation matrices with the higher-order singular value decomposition (HOSVD) method. The proposed PKM-HOSVD model is validated by extensive field experiments conducted for 4-by-4 MIMO systems in both indoor and outdoor environments. The results confirm that the statistic CSI varies slowly and the PKM-HOSVD will be helpful in the design of linear precoders. --Abstract, page iv

    Spatial Channel Degrees of Freedom for Optimum Antenna Arrays

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    One of the ultimate goals of future wireless networks is to maximize data rates to accommodate bandwidth-hungry services and applications. Thus, extracting the maximum amount of information bits for given spatial constraints when designing wireless systems will be of great importance. In this paper, we present antenna array topologies that maximize the communication channel capacity for given number of array elements while occupying minimum space. Capacity is maximized via the development of an advanced particle swarm optimization (PSO) algorithm devising optimum standardized and arbitrarily-shaped antenna array topologies. Number of array elements and occupied space are informed by novel heuristic spatial degrees of freedom (SDoF) formulations which rigorously generalize existing SDoF formulas. Our generalized SDoF formulations rely on the differential entropy of three-dimensional (3D) angle of arrival (AOA) distributions and can associate the number of array elements and occupied space for any AOA distribution. The proposed analysis departs from novel closed-form spatial correlation functions (SCFs) of arbitrarily-positioned array elements for all classes of 3D multipath propagation channels, namely, isotropic, omnidirectional, and directional. Extensive simulation runs and comparisons with existing trivial solutions verify correctness of our SDoF formulations resulting in optimum antenna array topologies with maximum capacity performance and minimum space occupancy

    Antenna Systems

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    This book offers an up-to-date and comprehensive review of modern antenna systems and their applications in the fields of contemporary wireless systems. It constitutes a useful resource of new material, including stochastic versus ray tracing wireless channel modeling for 5G and V2X applications and implantable devices. Chapters discuss modern metalens antennas in microwaves, terahertz, and optical domain. Moreover, the book presents new material on antenna arrays for 5G massive MIMO beamforming. Finally, it discusses new methods, devices, and technologies to enhance the performance of antenna systems

    Higher Rank Principal Kronecker Model for Triply Selective Fading Channels with Experimental Validation

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    This paper proposes a higher rank principal Kronecker model (PKM) for simulating triply selective fading channels. To construct the PKM, the channel correlation matrices are decomposed using the higher order singular value decomposition (HOSVD) method. The proposed PKM-HOSVD model improves upon the original Kronecker model by using higher rank approximation of the channel correlation matrices rather than the rank-1 approximation. The proposed PKM-HOSVD model was validated by extensive field experiments conducted for 4 x 4 multiple-input-multiple-output (MIMO) systems in both indoor and outdoor environments. The carrier frequencies used included 800 MHz, 2.2 GHz, and 5.2 GHz. The channel correlation matrices calculated from the measured channel coefficients were then decomposed via the proposed PKM-HOSVD method. The quality of the decomposition was evaluated by not only the mean square error but also the correlation matrix distance. These results indicate that many practical channels must use higher rank approximation rather than the commonly used rank-1 approximation (or the Kermoal method) to achieve satisfactory decomposition accuracy. In addition, the predicted channel capacity by the proposed channel simulation model achieves better accuracy than the original rank-1 channel simulation model

    Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

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    Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018
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