Joint Transmitter-receiver Optimization Research Articles

Joint Transmitter-Receiver Optimization and Self-Interference Suppression in Full-Duplex MIMO Systems

In this paper, we study the effects of joint transmit and receive antennas’ selection on full-duplex (FD) multiple-input-multiple-output (MIMO) networks’ performance. The antennas’ selection problem is, in general, a combinatorial problem whose complexity grows exponentially with the number of antennas. To fully understand the effects of antennas’ selection, we study the sum rate maximization problem in a single-cell network with an FD-MIMO base-station (BS). First, we consider a system with a normal-scale MIMO full-duplex BS, i.e., a normal-scale FD MIMO system. The sum rate maximization problem is studied for two different scenarios; in the first scenario, we consider jointly optimizing the transmit and receive antennas’ selection with the precoder and the receiver weights. A Generalized Bender's Decomposition based algorithm is proposed to solve the mixed-integer nonlinear sum rate maximization problem. In the second scenario, we consider self-interference cancellation via zero-forcing (ZF) transmission. A heuristic algorithm is proposed to solve the sum rate maximization problem by optimizing the selection of the transmit antennas, receive antennas, and the receive antennas at which self-interference is nulled. Second, in a very-large scale, i.e., massive MIMO system, we derive lower bounds for the uplink and downlink rates with ZF receiver and precoder, respectively. The sum rate is maximized by jointly optimizing the transmit to receive antennas ratio and the ratio of the receive antennas at which self-interference is nulled. Finally, via numerical analysis, we evaluate the performance of the formulated sum rate maximization problems.

Joint Transmitter–Receiver Optimization in Multitarget MIMO Radar

Although a significant attention has been drawn to the concept of multiple-input multiple-output (MIMO) radar and in particular on the transmit beamforming design and multitarget localization, the cooperation between the transmitter (Tx) and the receiver (Rx) has been rarely investigated. In this paper, a novel joint Tx and Rx optimization approach for localization is proposed for MIMO radar, where the transmit beamforming design and the estimation of the target's complex path gain are jointly derived by solving an optimization problem that takes account various target parameters. Moreover, the proposed transmit beamforming design controls the power distribution per individual target. The performance of the proposed method is evaluated using computer simulation studies and compared with techniques which simply combine Tx beamforming design with multitarget localization methods.

Radar Constant-Modulus Waveform Design with Prior Information of the Extended Target and Clutter.

Radar waveform design is of great importance for radar system performances and has drawn considerable attention recently. Constant modulus is an important waveform design consideration, both from the point of view of hardware realization and to allow for full utilization of the transmitter’s power. In this paper, we consider the problem of constant-modulus waveform design for extended target detection with prior information about the extended target and clutter. At first, we propose an arbitrary-phase unimodular waveform design method via joint transmitter-receiver optimization. We exploit a semi-definite relaxation technique to transform an intractable non-convex problem into a convex problem, which can then be efficiently solved. Furthermore, quadrature phase shift keying waveform is designed, which is easier to implement than arbitrary-phase waveforms. Numerical results demonstrate the effectiveness of the proposed methods.

Joint Transmitter–Receiver Frequency-Domain Equalization in Generalized Multicarrier Code-Division Multiplexing Systems

Joint transmitter-receiver optimization in generalized multicarrier code-division multiplexing (GMC-CDM) systems is investigated in this paper. The optimization consists of a one-tap post-frequency-domain equalizer (post-FDE) and a one-tap pre-FDE. While the one-tap post-FDE is optimized under the criterion of minimum mean square error (MMSE), the one-tap pre-FDE is achieved through three stages of optimization, which are operated at different levels and motivated to achieve, possibly, different objectives, including maximum throughput and maximum reliability. Specifically, in our three-stage pre-FDE, the first-stage pre-FDE is operated at the symbol level, concerning only the symbols within a group. The second-stage pre-FDE is carried out at the group level for harmonization among the groups. Finally, the third-stage pre-FDE handles group partition. In this paper, the error and throughput performance of the GMC-CDM systems is investigated when assuming communications over frequency-selective Rayleigh fading channels. It can be shown that the reliability or throughput of the GMC-CDM systems can be significantly improved by employment of the proposed pre- and post-FDE schemes. Furthermore, the pre- and post-FDE algorithms obtained can be implemented with high flexibility, which facilitates a GMC-CDM system to achieve a good tradeoff between its throughput and reliability.

Optimum Infinite-Length MMSE Multi-User Decision-Feedback Space-TimeProcessing in Broadband Cellular Radio

We present an investigation of space-time receiver architectures in multi-user wireless systems where optimal idealized (infinite-length) space-time filtering is applied to minimize the mean-square error (MSE). Feedforward, decision-feedback and cross-decision feedback filters are employed; hence, the system eliminates the post-cursor ISI (intersymbol interference) and CCI (co-channel interference). While this is a form of MIMO-DFE (Multi-Input Multi-Output Decision-Feedback Equalization), no joint transmitter-receiver optimization is performed since the transmit sources are assumed to be individual users. Our analysis leads to an entirely novel closed-form expression for the minimum achievable MSE for any single user in both fully- and partially-connected cross-decision feedback systems (XDF). This differs from previous results on MIMO-DFE obtained in a CDMA context which rely on the Gaussian assumption. Numerical results compare the performance of XDF systems with standard space-time DF and linear processing as well as the MIMO matched-filter bound in both a generic Rayleigh-fading system context and a broadband wireless context with fixed, highly directional subscriber antennas and correlated fading based on a 3D channel model parameterized according to measurements at 29.5 GHz. Results indicate that generally, an N-element array with fully-connected XDF processing provides the same performance as an N+1-element array with standard linear space-time processing.

Joint Transmitter-Receiver Optimization in the Downlink CDMA Systems

To maximize the downlink code-division multiple access (CDMA) system capacity, we propose to minimize the total transmitted power of the system subject to users′ signal-to-interference ratio (SIR) requirements via designing optimum transmitter sequences and utilizing linear optimum receivers (minimum mean square error (MMSE) receiver). In our work on joint transmitter-receiver design for the downlink CDMA systems with multiple antennas and multipath channels, we develop several optimization algorithms by considering various system constraints and prove their convergence. We empirically observed that under the optimization algorithm with no constraint on the system, the optimum receiver structure matches the received transmitter sequences. A simulation study is performed to see how the different practical system constraints penalize the system with respect to the optimum algorithm with no constraint on the system.

Joint Transmitter-Receiver Optimization in the Downlink CDMA Systems

Joint Transmitter-Receiver Optimization in the Downlink CDMA Systems

Joint transmitter-receiver optimization for partial response channels based on nonmaximally decimated filterbank precoding technique

Transmitter and receiver filter design plays a key role in communication systems with partial response channels. For a partial response system, a nonmaximally decimated multirate filter bank can be used as a precoder. Based on the MMSE criterion, a closed-form solution to the joint transmitter-receiver optimization problem for noisy partial response channels is presented in this paper. It is found that the redundancy introduced by the nonmaximally decimated filter bank precoder can compensate for spectral nulls in partial response channels that can impair several known joint optimization methods. Simulation results corroborate the analysis that joint transmitter-receiver optimization can achieve significant performance improvement over inverse filter receiver and receiver optimization schemes.

Joint transmitter-receiver optimization in synchronous multiuser communications over multipath channels

Transmitter optimization, in addition to receiver optimization, contributes significantly to efficient interference suppression in multiple access and multipath channels. The system design is based on the joint optimization of the transmitter and the receiver in a synchronous multiuser channel characterized by multipath propagation. Joint optimization is represented by a linear transformation of the transmitted signals at the transmitter and a linear transformation of received signals at each receiving site that minimize the effect of multiple access and multipath interference. The minimum mean squared error between the true bit value and its estimate at the output of the receiver is taken as the cost function, subject to average and peak transmit power constraints. It is shown that joint transmitter-receiver optimization outperforms significantly either transmitter optimization or receiver-based techniques. The crucial assumption, in the case of multipath channels, is that the transmitter knows the multipath characteristics of all channels and that the channel dynamics are sufficiently slow so that multipath profiles remain essentially constant over a block of preceded bits. The practical applications can be found in indoor and cellular communications, satellite communications, or military communications where nonorthogonal signature waveforms are employed.

Joint transmitter-receiver optimization for multi-input multi-output systems with decision feedback

The joint transmit-receive optimization problem for multiuser communication systems with decision feedback is investigated. It is shown that minimization of the geometric mean-squared error (defined as the determinant of the error covariance matrix) leads to a tractable transmitter optimization problem for general multi-input multi-output decision-feedback systems. Several computational results are included that highlight system performance for a variety of useful transmission scenarios. >