Joint Optimization Of Transmitter Research Articles

A MMSE Vector Precoding with Block Diagonalization for Multiuser MIMO Downlink

Block diagonalization (BD) algorithm is a generalization of the channel inversion that converts multiuser multi-input multi-output (MIMO) broadcast channel into single-user MIMO channel without inter-user interference. In this paper, we combine the BD technique with a minimum mean square error vector precoding (MMSE-VP) for achieving further gain in performance with minimal computational overhead. Two key ingredients to make our approach effective are the QR decomposition based block diagonalization and joint optimization of transmitter and receiver parameters in the MMSE sense. In fact, by optimizing precoded signal vector and perturbation vector in the transmitter and receiver jointly, we pursue an optimal balance between the residual interference mitigation and the noise enhancement suppression. From the sum rate analysis as well as the bit error rate simulations (both uncoded and coded cases) in realistic multiuser MIMO downlink, we show that the proposed BD-MVP brings substantial performance gain over existing multiuser MIMO algorithms.

Joint Transmitter and Receiver Optimization in Additive Cyclostationary Noise

A joint optimization of transmitter and receiver is considered for strictly band-limited linear modulations in additive cyclostationary noise. Under the assumptions that the period of the cyclostationarity of the noise is the same as the inverse of the symbol transmission rate and that the noise has a positive-definite autocorrelation function, the optimum transmitter and receiver waveforms that jointly minimize the mean-squared error at the output of the linear receiver are derived with the data sequence modeled as a wide-sense stationary (WSS) colored random process and the channel modeled as a linear time-invariant system with a general frequency-selective impulse response. Numerical results show that this joint optimization technique leads to a significant performance improvement over the systems with receiver-only optimization and the systems with no transmitter and receiver optimizations.

Modulation by means of linear periodic filtering

Linear periodically time-varying filters are considered as modulators and demodulators for the transmission of analog information over a stationary Gaussian channel. A complete analysis is carried out based on a certain general decomposition of such a filter into a number of branches, each containing a linear time-invariant filter and a multiplication with a complex sinusoid. Receiver optimization is carried out under the assumption that the above decomposition is finite. Finally, a joint optimization of transmitter and receiver is derived under the further restriction that the message signal is strictly band-limited.

Joint optimization of transmitter and receiver filters in digital PAM systems with a Viterbi detector

Joint optimization of transmitter and receiver filters in a pulse-amplitude modulation (PALM) system with an arbitrary but fixed Viterbi detector is considered. Optimization is performed under an average transmitted power constraint with respect to a new criterion called the effective mean-square error (EMSE). It is shown that the optimization problem is convex. A necessary and sufficient condition for optimality is derived, and a method for optimization is proposed. Numerical results are obtained for a channel with coaxial cable characteristics.

Nyquist's problem—The joint optimization of transmitter and receiver in pulse amplitude modulation

Using a criterion of minimum mean square interference, the optimum, linear, generally unrealizable receiver for a noisy pulse amplitude modulation (PAM) system is specified for the case in which a finite number of identically shaped pulses with random, possibly correlated amplitudes are transmitted. The interference is composed of both noise and intersymbol interference. The optimum receiver, using the same criterion, is also obtained for the case in which the intersymbol interference is constrained to be zero. The average error probabilities associated with these receivers are compared with each other and with a matched filter receiver in one example. In addition, formulas for optimum transmitted pulse shapes are derived, and the joint optimization of transmitter and receiver is carried out in detail for the case of signaling through a noisy RC filter. Other formulas enable one to explore the dependence of the minimum mean square interference on the data rate, the noise spectrum, the impulse response of the transmission medium, and the autocorrelation of the message sequence.