The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

A Kavcic - One of the best experts on this subject based on the ideXlab platform.

  • approaching the capacity of the mimo rayleigh Flat Fading Channel with qam constellations independent across antennas and dimensions
    IEEE Transactions on Wireless Communications, 2006
    Co-Authors: J Bellorado, S S Ghassemzadeh, A Kavcic
    Abstract:

    In this study we consider the challenge of reliable communication over a wireless Rayleigh Flat-Fading Channel using multiple transmit and receive antennas. Since modern digital communication systems employ signal sets of finite cardinality, we examine the use of the quadrature amplitude modulation (QAM) constellation to approach the capacity of this Channel. By restricting the Channel input to the M-QAM subset of the complex-plane, the maximum achievable information rate (CM-QAM ) is strictly bounded away from the Channel capacity (C). We utilize a modified version of the Arimoto-Blahut algorithm to determine CM-QAM and the probability distribution over the Channel input symbols that achieves it. The results of this optimization procedure numerically indicate that the optimal input symbol distribution factors into the product of identical distributions over each real dimension of the transmitted signal. This is shown to vastly reduce the computational complexity of the optimization algorithm. Furthermore, we utilize the computed optimal Channel input probability mass function (pmf) to construct capacity approaching trellis codes. These codes are implemented independent across all antennas and symbol dimensions and, if used as inner codes to outer low-density parity check (LDPC) codes, can achieve arbitrarily small error rates at signal-to-noise ratios very close to the Channel capacity CM-QAM . Examples are given for a 2-transmit/2-receive antenna (2 times 2) system

  • approaching the capacity of the mimo rayleigh Flat Fading Channel with qam constellations independent across antennas and dimensions
    International Symposium on Information Theory, 2003
    Co-Authors: J Bellorado, A Kavcic
    Abstract:

    In this study we consider the challenge of reliable communication over a wireless Rayleigh Flat-Fading Channel using multiple transmit and receive antennas. Since modern digital communication systems employ signal sets of finite cardinality, we examine the use of the Quadrature Amplitude Modulation (QAM) constellation to approach the capacity of this Channel. By restricting the Channel input to the M-QAM subset of the complex-plane, the maximum achievable information rate (CM-QAM) is strictly bounded away from the Channel capacity (C). We utilize a modified version of the Arimoto-Blahut al- gorithm to determine CM-QAM and the probability distribution over the Channel input symbols that achieves it. The results of this optimization procedure numerically indicate that the optimal input symbol distribution factors into the product of identical distributions over each real dimension of the transmitted signal. This is shown to vastly reduce the computational complexity of the optimization algorithm. Furthermore, we utilize the computed optimal Channel input probability mass function (pmf) to construct capacity approaching trellis codes. These codes are implemented independent across all antennas and symbol dimensions and, if used as inner codes to outer low-density parity check (LDPC) codes, can achieve arbitrarily small error rates at signal-to-noise ratios very close to the Channel capacity CM-QAM. Examples are given for a 2-transmit/2-receive antenna (2 × 2) system.

A K Chaturvedi - One of the best experts on this subject based on the ideXlab platform.

  • fractional timing offset and Channel estimation for mimo ofdm systems over Flat Fading Channels
    Wireless Communications and Networking Conference, 2012
    Co-Authors: Uma R Mahesh, A K Chaturvedi
    Abstract:

    This paper addresses the problem of fractional timing offset and Channel estimation in Multiple input Multiple output orthogonal frequency division multiplexing (MIMO OFDM) systems. The estimators have been derived assuming a Flat Fading Channel and using the maximum likelihood criterion. Closed form Cramer Rao bound (CRB) expressions for fractional timing offset and Channel response are also derived. Simulation results have been used to cross-check the accuracy of the proposed estimation algorithm.

  • fractional timing offset and Channel estimation in ofdm systems over Flat Fading Channels
    National Conference on Communications, 2011
    Co-Authors: Uma R Mahesh, A K Chaturvedi
    Abstract:

    This paper addresses the estimation of fractional timing offset and Channel response in orthogonal frequency division multiplexing (OFDM) systems. Timing offset and Channel estimator is derived based on maximum likelihood criterion. Closed form Cramer Rao bound (CRB) expressions for fractional timing offset and Channel response are derived. We consider Flat Fading Channel throughout this paper. Simulation results have been used to cross-check the accuracy of the proposed estimation algorithm.

J Bellorado - One of the best experts on this subject based on the ideXlab platform.

  • approaching the capacity of the mimo rayleigh Flat Fading Channel with qam constellations independent across antennas and dimensions
    IEEE Transactions on Wireless Communications, 2006
    Co-Authors: J Bellorado, S S Ghassemzadeh, A Kavcic
    Abstract:

    In this study we consider the challenge of reliable communication over a wireless Rayleigh Flat-Fading Channel using multiple transmit and receive antennas. Since modern digital communication systems employ signal sets of finite cardinality, we examine the use of the quadrature amplitude modulation (QAM) constellation to approach the capacity of this Channel. By restricting the Channel input to the M-QAM subset of the complex-plane, the maximum achievable information rate (CM-QAM ) is strictly bounded away from the Channel capacity (C). We utilize a modified version of the Arimoto-Blahut algorithm to determine CM-QAM and the probability distribution over the Channel input symbols that achieves it. The results of this optimization procedure numerically indicate that the optimal input symbol distribution factors into the product of identical distributions over each real dimension of the transmitted signal. This is shown to vastly reduce the computational complexity of the optimization algorithm. Furthermore, we utilize the computed optimal Channel input probability mass function (pmf) to construct capacity approaching trellis codes. These codes are implemented independent across all antennas and symbol dimensions and, if used as inner codes to outer low-density parity check (LDPC) codes, can achieve arbitrarily small error rates at signal-to-noise ratios very close to the Channel capacity CM-QAM . Examples are given for a 2-transmit/2-receive antenna (2 times 2) system

  • approaching the capacity of the mimo rayleigh Flat Fading Channel with qam constellations independent across antennas and dimensions
    International Symposium on Information Theory, 2003
    Co-Authors: J Bellorado, A Kavcic
    Abstract:

    In this study we consider the challenge of reliable communication over a wireless Rayleigh Flat-Fading Channel using multiple transmit and receive antennas. Since modern digital communication systems employ signal sets of finite cardinality, we examine the use of the Quadrature Amplitude Modulation (QAM) constellation to approach the capacity of this Channel. By restricting the Channel input to the M-QAM subset of the complex-plane, the maximum achievable information rate (CM-QAM) is strictly bounded away from the Channel capacity (C). We utilize a modified version of the Arimoto-Blahut al- gorithm to determine CM-QAM and the probability distribution over the Channel input symbols that achieves it. The results of this optimization procedure numerically indicate that the optimal input symbol distribution factors into the product of identical distributions over each real dimension of the transmitted signal. This is shown to vastly reduce the computational complexity of the optimization algorithm. Furthermore, we utilize the computed optimal Channel input probability mass function (pmf) to construct capacity approaching trellis codes. These codes are implemented independent across all antennas and symbol dimensions and, if used as inner codes to outer low-density parity check (LDPC) codes, can achieve arbitrarily small error rates at signal-to-noise ratios very close to the Channel capacity CM-QAM. Examples are given for a 2-transmit/2-receive antenna (2 × 2) system.

Uma R Mahesh - One of the best experts on this subject based on the ideXlab platform.

  • fractional timing offset and Channel estimation for mimo ofdm systems over Flat Fading Channels
    Wireless Communications and Networking Conference, 2012
    Co-Authors: Uma R Mahesh, A K Chaturvedi
    Abstract:

    This paper addresses the problem of fractional timing offset and Channel estimation in Multiple input Multiple output orthogonal frequency division multiplexing (MIMO OFDM) systems. The estimators have been derived assuming a Flat Fading Channel and using the maximum likelihood criterion. Closed form Cramer Rao bound (CRB) expressions for fractional timing offset and Channel response are also derived. Simulation results have been used to cross-check the accuracy of the proposed estimation algorithm.

  • fractional timing offset and Channel estimation in ofdm systems over Flat Fading Channels
    National Conference on Communications, 2011
    Co-Authors: Uma R Mahesh, A K Chaturvedi
    Abstract:

    This paper addresses the estimation of fractional timing offset and Channel response in orthogonal frequency division multiplexing (OFDM) systems. Timing offset and Channel estimator is derived based on maximum likelihood criterion. Closed form Cramer Rao bound (CRB) expressions for fractional timing offset and Channel response are derived. We consider Flat Fading Channel throughout this paper. Simulation results have been used to cross-check the accuracy of the proposed estimation algorithm.

Richard D Wesel - One of the best experts on this subject based on the ideXlab platform.

  • joint iterative Channel estimation and decoding in Flat correlated rayleigh Fading
    IEEE Journal on Selected Areas in Communications, 2001
    Co-Authors: Christos Komninakis, Richard D Wesel
    Abstract:

    This paper addresses the design and performance evaluation with respect to capacity of M-PSK turbo-coded systems operating in frequency-Flat time-selective Rayleigh Fading. The receiver jointly performs Channel estimation and turbo decoding, allowing the two processes to benefit from each other. To this end, we introduce a suitable Markov model with a finite number of states, designed to approximate both the values and the statistical properties of the correlated Flat Fading Channel phase, which poses a more severe challenge to PSK transmission than amplitude hiding. Then, the forward-backward algorithm determines both the maximum a posteriori probability (MAP) value for each symbol in the data sequence and the MAP Channel phase in each iteration. Simulations show good performance in standard correlated Rayleigh Fading Channels. A sequence of progressively tighter upper bounds to the capacity of a simplified Markov-phase Channel is derived, and performance of a turbo code with joint iterative Channel estimation and decoding is demonstrated to approach these capacity bounds.

  • pilot aided joint data and Channel estimation in Flat correlated Fading
    Global Communications Conference, 1999
    Co-Authors: Christos Komninakis, Richard D Wesel
    Abstract:

    This paper addresses the design and performance evaluation of a pilot-aided turbo-coded system to achieve reliable PSK communication in frequency-Flat, time-selective Fading, with a relatively high Doppler rate. We introduce a suitable Markov model with a finite number of states, designed to approximate both the values and the statistical properties of the correlated Flat Fading Channel phase, which poses a more severe challenge to PSK transmission than amplitude Fading. The forward-backward algorithm is used to determine both the maximum a posteriori probability (MAP) value for each bit in the data sequence, and the MAP Channel phase in each iteration. Soft information is exchanged between the phase and data estimation modules. Using a turbo-code and joint iterative decoding and Channel estimation, performance is demonstrated to approach an upper bound to the capacity of a Markov-phase Channel.