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Zero-Forcing DFE Transceiver Design Over Slowly Time-Varying MIMO Channels Using ST-GTD

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2010年第11期58卷 5779-5790页

作者： Liu, Chih-Hao Vaidyanathan, Palghat P. CALTECH Pasadena CA 91125 USA

This paper considers the optimization of transceivers with decision feedback equalizers (DFE) for slowly time-varying memoryless multi-input multi-output (MIMO) channels. The data vectors are grouped into space-time blocks (ST-blocks) for the spatial and temporal precoding to take advantage of the diversity offered by time-varying channels. The space-time generalized triangular decomposition (ST-GTD) is proposed for application in time-varying channels. Under the assumption that the instantaneous channel state information at the transmitter (CSIT) and receiver (CSIR), and the channel prediction are available, we also propose the space-time geometric mean decomposition (ST-GMD) system based on ST-GTD. Under perfect channel prediction, the system minimizes both the arithmetic MSE at the feedback detector, and the average un-coded bit error rate (BER) in moderate high signal to noise ratio (SNR) region. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD system is also proposed. At the moderate high SNR region, our analysis and numerical results show that all the proposed systems have better BER performance than the conventional GMD-based systems over time-varying channels;the average BERs of the proposed systems are non-increasing functions of the ST-block size.

关键词： generalized triangular decomposition GMD space-time GTD time-varying channels transceivers

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Intelligent based hybrid precoder for millimetre wave massive MIMO system

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WIRELESS NETWORKS 2024年第6期30卷 5239-5246页

作者： Rajarajeswarie, B. Sandanalakshmi, R. Puducherry Technol Univ Dept Elect & Commun Engn Pondicherry India

The Millimeter-wave and Massive Multiple Input Multiple Output technologies are promising candidates to offer high data rates and system throughputs in the next-generation wireless communication systems. In massive MIMO systems, the precoder plays a leading role to cancel the interference between the data stream and thereby reduce the complexity of the receiver design. In the conventional fully digital precoding scheme, many Radio Frequency chains are essential for every antenna array. Therefore, a hybrid precoder is a feasible solution to reduce the RF chains and improve the antenna array gain by dividing the signal processing into analog and digital precoders. Designing a hybrid precoder is a non-convex optimization problem because the phase shifter in the analog precoder holds hardware constraints. To address this, an intelligent hybrid precoder is designed using deep learning algorithms. In this paper, the Deep Learning framework is incorporated for hybrid precoder as it renovates non-convex problems into a network training process. In this work, the hybrid precoder is based on decomposition techniques such as Uniform Channel decomposition (UCD) and generalized triangular decomposition method, which is implemented in the training process as it provides equal gain for all subchannels to diminish the inter subchannel interference. The simulation results validate the proposed work is superior in terms of the Bit Error Rate in comparison with other conventional decomposition techniques. The result shows that the deep learning-based hybrid precoder is better than the conventional with a 2 dB improvement between the UCD method and GMD method.

关键词： Millimeter wave Massive MIMO Hybrid precoding Uniform channel decomposition generalized triangular decomposition Deep learning

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THE ROLE OF GTD IN OPTIMIZING BIORTHOGONAL FILTER BANKS

THE ROLE OF GTD IN OPTIMIZING BIORTHOGONAL FILTER BANKS

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Weng, Ching-Chih Vaidyanathan, P. P. CALTECH Dept Elect Engn Pasadena CA 91125 USA

ISBN: (纸本)9781457705397

Filter bank optimization for specific input statistics has been of great interest in both theory and practice in many signal processing applications. In this paper we consider biorthogonal GTD (generalized triangular decomposition) filter banks for optimizing the coding gain. We develop some theoretical results for the optimal biorthogonal GTD subband coder. We also show in both theory and numerical simulations that biorthogonal GTD subband coders have superior performance than biorthogonal subband coders, orthonormal GTD subband coders, and orthonormal subband coders. In addition, the uniform bit loading scheme can with no loss of optimality be used in the optimal biorthogonal GTD coders, which does not have the granularity problem arising in the conventional optimum bit loading formula.(1)

关键词： Multirate signal Processing Filter Banks Subband Coding generalized triangular decomposition

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A Novel Structure for MMSE Transceivers over Slowly Time-varying Channels

A Novel Structure for MMSE Transceivers over Slowly Time-var...

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44th Asilomar Conference on Signals, Systems and Computers

作者： Liu, Chih-Hao Vaidyanathan, P. P. CALTECH Dept Elect Engn Pasadena CA 91125 USA

ISBN: (纸本)9781424497218

This paper addresses the design problem of decision feedback (DF) transceiver without zero-forcing constraint over slowly time-varying narrowband multi-input multi-output (MIMO) channels. The space-time generalized triangular decomposition (ST-GTD) is applied for the design of minimum mean square error (MMSE) DF transceiver. With space-time powerloading, the proposed space-time geometric mean decomposition (ST-GMD) MMSE transceiver maximizes Gaussian mutual information over the equivalent channel seen by each space-time block. For practical applications, the causal ST-GTD MMSE transceiver which does not require channel prediction but shares the same asymptotic bit error rate (BER) performance with the ST-GMD MMSE system is also developed. In high signal to interference plus noise ratio (SINR) region, our results show that the proposed MMSE transceivers have better BER performance than the conventional GMD-based MMSE transceiver;the average BERs of the proposed systems are a non-increasing function of the ST-block size.(1)

关键词： generalized triangular decomposition Transceivers GMD Time-Varying Channels Space-time GTD

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Precoder optimization for Nonlinear MIMO transceiver based on arbitrary cost function

Precoder optimization for Nonlinear MIMO transceiver based o...

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41st Annual Conference on Information Sciences and Systems (CISS 2007)

作者： Jiang, Yi Palomar, Daniel P. Varanasi, Mahesh K. Univ Colorado Dept ECE Boulder CO 80309 USA Hong Kong Univ Sci & Technol Dept ECE Kowloon Peoples R China

ISBN: (纸本)9781424410361

Assuming full channel state information (CSI) at both transmitter (CSIT) and receiver (CSIR), we consider optimizing a nonlinear MIMO transceiver with decision feedback equalizer (DFE) with respect to some global cost function fo. Setting the receiver to be a minimum mean-squared error (MMSE) DFE, the MIMO transceiver optimization problem reduces to optimizing a linear precoder. Based on the generalized triangular decomposition (GTD) and majorization theory, we prove that for any cost function fo the optimum precoder is of the same special structure and hence the original complicated matrix optimization problem can be significantly simplified to an optimization problem with scalar-valued variables. Furthermore, if the cost function is specialized to the cases where the composite function fo o exp is either Schur-convex or Schur-concave, then the nonlinear transceiver design becomes exceedingly simple. In particular, when fo o exp is Schur-convex, the optimum nonlinear transceiver design turns out to be the uniform channel decomposition (UCD) scheme;when fo o exp is Schur-concave, the optimum nonlinear design degenerates to linear diagonal transmission.

关键词： MIMO transceiver optimization generalized triangular decomposition majorization theory Schur-convex

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Joint Optimization of Transceivers with Decision Feedback and Bit Loading

Joint Optimization of Transceivers with Decision Feedback an...

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42nd Asilomar Conference on Signals, Systems and Computers

作者： Weng, Ching-Chih Chen, Chun-Yang Vaidyanathan, P. P. CALTECH Dept Elect Engn Pasadena CA 91125 USA

ISBN: (纸本)9781424429400

The transceiver optimization problem for MIMO channels has been considered in the past with linear receivers as well as with decision feedback (DFE) receivers. Joint optimization of bit allocation, precoder, and equalizer has in the past been considered only for the linear transceiver (transceiver with linear precoder and linear equalizer). It has also been observed that the use of DFE even without bit allocation in general results in better performance that linear transceivers with bit allocation. This paper provides a general study of this for transceivers with the zero-forcing constraint. It is formally shown that when the bit allocation, precoder, and equalizer are jointly optimized, linear transceivers and transceivers with DFE have identical performance in the sense that transmitted power is identical for a given bit rate and error probability. The developments of this paper are based on the generalized triangular decomposition (GTD) recently introduced by Jiang, Li, and Hager. It will be shown that a broad class of GTD-based systems solve the optimal DFE problem with bit allocation. The special case of a linear transceiver with optimum bit allocation will emerge as one of the many solutions.(1)

关键词： Decision Feed-Back BER Optimization generalized triangular decomposition Bit Allocation MIMO Transceiver

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Decision feedback based transceiver optimization for MIMO intersymbol interference channels

Decision feedback based transceiver optimization for MIMO in...

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41st Asilomar Conference on Signals, Systems and Computers

作者： Jiang, Yi Varanasi, Mahesh K. Palomar, Daniel P. NextWave Broadband San Diego CA 92130 USA Univ Colorado Boulder CO 80309 USA Univ Colorado Dept ECE Boulder CO 80309 USA Hong Kong Univ Sci & Technol Dept ECE Kowloon Peoples R China

ISBN: (纸本)9781424421091

This paper deals with optimizing a transceiver, which consists of a linear time invariant (LTI) matrix filter at the transmitter and a decision feedback (DF) receiver, for single-carrier data transmission over multi-input multi-output (MIMO) intersymbol interference (ISI) channels. Considering a spatial multiplexing approach for transmission of multiple scalar substreams, we adopt some cost function f(0)({MSEi}) to measure the overall system performance, where MSEi's are the mean-squared errors (MSE) of the substreams. It is proven that for any cost function fo the optimum transmitter is of the same specific structure and the original complicated variational optimization problem can be drastically simplified to a problem with scalar variables. The solution can be further simplified if the cost function is specialized to the cases where the composite function f(0) o exp is either Schur-convex or Schur-concave.

关键词： MIMO transceiver optimization generalized triangular decomposition ISI channels majorization theory Schur-convexity single-carrier transmission

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Decorrelating transforms for spectral vector quantization

Decorrelating transforms for spectral vector quantization

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18th International Conference on Digital Signal Processing (DSP)

作者： Ramirez, Miguel Arjona Univ Sao Paulo Escola Politecn Dept Elect Syst Engn Sao Paulo Brazil

ISBN: (纸本)9781467358057

Split vector quantization (SVQ) performs well and efficiently for line spectral frequency (LSF) quantization, but misses some component dependencies. Switched SVQ (SSVQ) can restore some advantage due to nonlinear dependencies through Gaussian Mixture Models (GMM). Remaining linear dependencies or correlations between vector components can be used to advantage by transform coding. The Karhunen-Loeve transform (KLT) is normally used but eigendecomposition and full transform matrices make it computationally complex. However, a family of transforms has been recently characterized by the capability of generalized triangular decomposition (GTD) of the source covariance matrix. The prediction-based lower triangular transform (PLT) is the least complex of such transforms and is a component in the implementation of all of them. This paper proposes a minimum noise structure for PLT SVQ. Coding results for 16-dimensional LSF vectors from wideband speech show that GMM PLT SSVQ can achieve transparent quantization down to 41 bit/frame with distortion performance close to GMM KLT SSVQ at about three-fourths as much operational complexity. Other members of the GTD family, such as the geometric mean decomposition (GMD) transform and the bidiagonal (BID) transform, fail to capitalize on their advantageous features due to the low bit rate per component in the range tested.

关键词： Gaussian mixture models generalized triangular decomposition Karhunen-Loeve transform linear prediction line spectral frequencies prediction-based lower triangular transform switched split vector quantization

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Adaptive Joint Nonlinear Transmit-Receive Processing for Multi-Cell MIMO Networks

Adaptive Joint Nonlinear Transmit-Receive Processing for Mul...

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IEEE Global Communications Conference (GLOBECOM)

作者： Sun, Liang Lei, Ming NEC Labs China Beijing 100084 Peoples R China

ISBN: (纸本)9781467309219;9781467309202

This paper considers signal processing algorithms for the downlink coordinated multi-point multiple-input multiple-output (MIMO) systems with multiple-antenna users. A novel adaptive joint nonlinear transmit-receive processing algorithm is proposed based on zero-forcing (ZF) criterion. In this algorithm, a block successive ZF precoding is first applied at the multiple base stations to pre-cancel partial multiuser interference. Then nonlinear Tomlinson-Harashima precoding is applied to further reduce interference between the data streams of other users and the other data streams of the same user, whereas linear equalization and modulo operation are applied at each user. We first show that the proposed joint nonlinear transmit-receive processing algorithm effectively decomposes the multiuser MIMO channel into parallel independent single-user MIMO channels. Different from the method in [1], our proposed algorithm allows the number of sub-channels of each user to be arbitrary number no more than the rank of that user's equivalent channel, and then for the given set of the numbers of sub-channels and the given power allocation of all users, closed-form expressions of the transmit and receive processing matrices are derived to optimize the output signal to interference plus noise ratio of each user. Subsequently, an adaptive method is proposed to adapt the number of sub-channels according to the fading of the users' channel matrices (termed as adaptive algorithm). Simulation results show that the proposed algorithm achieves much better throughput performance than the processing methods in the literature, such as the non-adaptive nonlinear preprocessing algorithm in [1] and the known block diagonalization techniques.

关键词： MIMO Tomlinson-Harashima precoding coordinated multi-point generalized triangular decomposition zero-forcing

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GTD-Based Transceivers for Decision Feedback and Bit Loading

GTD-Based Transceivers for Decision Feedback and Bit Loading

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Weng, Ching-Chih Chen, Chun-Yang Vaidyanathan, P. P. CALTECH Dept Elect Engn Pasadena CA 91125 USA

ISBN: (纸本)9781424423538

We consider new optimization problems for transceivers with DFE receivers and linear precoders, which also use bit loading at the transmitter. First, we consider the MIMO QoS (quality of service) problem, which is to minimize the total transmitted power when the bit rate and probability of error of each data stream are specified. The developments of this paper are based on the generalized triangular decomposition (GTD) recently introduced by Jiang, Li, and Hager. It is shown that under some multiplicative majorization conditions there exists a custom GTD-based transceiver which achieves the minimal power. The problem of maximizing the bit rate subject to the total power constraint and given error probability is also considered in this paper. It is shown that the GTD-based systems also give the optimal solutions to the bit rate maximization problem.(1)

关键词： Decision Feed-Back BER Optimization generalized triangular decomposition Bit Allocation MIMO Transceiver

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