Multimode Precoding Research Articles

Adaptive multimode precoding for ultra-broadband vectored DSL systems

In the downstream of a digital subscriber line (DSL) system transmitting over a large bandwidth, the row-wise diagonally dominant (RWDD) characteristic of the copper channel matrix, which holds at low frequencies, may not be valid at high frequencies because of the presence of strong crosstalk. Consequently, linear precoders result in sub-optimal bit-rate performance whilst the optimal non-linear precoders incur high computational complexity. In this work, we investigate a quad-mode precoder (QMP) which selectively operates on one of four modes on each frequency tone. A block-based adaptation strategy is introduced for complexity reduction whereby mode selection is invoked adaptively over blocks of tones. The computational complexity associated with the proposed precoder is analyzed and quantified against existing precoders. Results demonstrate that by suitably adapting the operating mode and block length of the proposed QMP according to the channel conditions, moderate computational saving could be attained without compromising the bit-rate performance. More importantly, the QMP facilitates green DSL as energy savings are feasible when some tones are de-activated to conserve energy.

Multimode precoding for crosstalk mitigation in ultra‐broadband DSL systems

SummaryThe achievable downstream bit‐rate performance of digital subscriber line (DSL) channels using low‐complexity linear precoders is suboptimal when the row‐wise diagonally dominant property of the channel matrix does not hold at high frequencies anticipated to be exploited in future‐generation DSL systems, while the optimal nonlinear precoder is computationally demanding. In this paper, we propose two multimode precoders, which are operable in four modes on each tone. Specifically, the proposed precoding strategies exploit the insertion loss and crosstalk information inferred from the channel matrix to execute mode selection for all the transmission tones. The computational complexity of the proposed multimode precoders is derived and compared with existing precoders. Simulation results show that the proposed precoders can achieve near‐optimal performance at a lower computational complexity.

Multimode Precoding for Multiuser MIMO Systems With Finite Rate Feedback

In practical multiuser multiple-input multiple-output (MU-MIMO) systems with limited feedback, inter-user interference cannot be completely suppressed due to the channel state information quantization error, and the residual interference degrades the throughputs. In this letter, we introduce a MU-MIMO system with multimode precoding that adapts the number of served users based on the channel condition to maximize the spectral efficiency. In addition, a mode selection rule and a novel cumulative distribution function-based feedback rule are also developed for the proposed system. Simulation results show that the proposed system provides higher spectral efficiency compared to conventional limited feedback precoding systems.

Energy Efficient Spectrum Sharing Strategy Selection for Cognitive MIMO Interference Channels

In this paper, we propose a promising discrete game-theoretic framework for distributed energy efficient discrete spectrum sharing strategy selection (i.e., joint discrete power control and multimode precoding strategy selection) with limited feedback for cognitive MIMO interference channels. Given the competitive nature, the secondary users are assumed to be selfish and noncooperative, each of whom attempts to maximize its individual energy efficiency under a minimum data rate constraint and an interference power constraint. A mechanism for shutting down links is proposed to reduce interference and save energy. A payoff function is designed to guarantee the feasibility of the pure strategy Nash equilibrium with no need to know the infeasible strategy profiles (a spectrum sharing strategy profile is said to be feasible if the stated constraints are satisfied; otherwise, the spectrum sharing strategy profile is said to be infeasible, i.e., they may not satisfy the interference power constraint and minimum data rate constraint) in advance. We then investigate the existence and the feasibility of the pure strategy Nash equilibrium, and further devise a pricing-based distributed algorithm for spectrum strategy selection. The proposed algorithm is proved to converge to a feasible pure strategy Nash equilibrium under specific conditions. Moreover, by studying the relationship between our proposed game and the social optimum, we find that the pricing mechanism can result in Pareto improvement and lead to better convergence for the proposed distributed algorithm. Numerical results show that our designed algorithm significantly outperforms the random selection algorithm and the pricing mechanism has a dramatic effect in improving the system performance.

Noncooperative Multimode Precoding with Limited Feedback in MIMO Interference Channels

This letter proposes an iterative multimode precoding scheme with limited feedback for nonreciprocal MIMO interference channels. Based on analysis of game theory, we model the iterative multimode precoding as a noncooperative game with a finite set of strategies. Numerical results are presented to verify the sum rate performance of the proposed scheme.

Game Theoretic Multimode Precoding Strategy Selection for MIMO Multiple Access Channels

This paper is concerned with decentralized selection of multimode precoding strategy for multiple-input multiple-output (MIMO) multiple access channels. We formulate it as a discrete noncooperative game. This game is shown to possess at least one pure strategy Nash equilibrium (NE) and the optimal strategy profile which maximizes the sum rate constitutes a pure strategy NE. Then we propose a decentralized algorithm based on learning automata to achieve the NE. A repeated mechanism is introduced to improve the sum rate performance and a mechanism for adapting step size is designed to control the convergence speed. Simulation results show that the proposed algorithm, which only requires limited feedback, can achieve near optimal or optimal sum rate performance.

Quantized Multimode Precoding in Spatially Correlated Multiantenna Channels

Multimode precoding, where the number of independent data-streams is adapted optimally, can be used to maximize the achievable throughput in multi-antenna communication systems. Motivated by standardization efforts embraced by the industry, the focus of this work is on systematic precoder design with realistic assumptions on the spatial correlation, channel state information (CSI) at the transmitter and the receiver, and implementation complexity. For spatial correlation of the channel matrix, we assume a general channel model, based on physical principles, that has been verified by many recent measurement campaigns. We also assume a coherent receiver and knowledge of the spatial statistics at the transmitter along with the presence of an ideal, low-rate feedback link from the receiver to the transmitter. The reverse link is used for codebook-index feedback and the goal of this work is to construct precoder codebooks, adaptable in response to the statistical information, such that the achievable throughput is significantly enhanced over that of a fixed, non-adaptive, i.i.d. codebook design. We illustrate how a codebook of semiunitary precoder matrices localized around some fixed center on the Grassmann manifold can be skewed in response to the spatial correlation via low-complexity maps that can rotate and scale submanifolds on the Grassmann manifold. The skewed codebook in combination with a lowcomplexity statistical power allocation scheme is then shown to bridge the gap in performance between a perfect CSI benchmark and an i.i.d. codebook design.

Interpolation-Based Multi-Mode Precoding for MIMO-OFDM Systems with Limited Feedback

Spatial multiplexing with multi-mode precoding provides a means to achieve both high capacity and high reliability in multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. Multi-mode precoding uses linear transmit precoding that adapts the number of spatial multiplexing data streams or modes, according to the transmit channel state information (CSI). As such, it typically requires complete knowledge of the multi-mode precoding matrices for each subcarrier at the transmitter. In practical scenarios where the CSI is acquired at the receiver and fed back to the transmitter through a low-rate feedback link, this requirement may entail a prohibitive feedback overhead. In this paper, we propose to reduce the feedback requirement by combining codebook-based precoder quantization, to efficiently quantize and represent the optimal precoder on each subcarrier, and multi-mode precoder frequency down-sampling and interpolation, to efficiently reconstruct the precoding matrices on all subcarriers based on the feedback of the indexes of the quantized precoders only on a fraction of the subcarriers. To enable this efficient interpolation-based quantized multimode precoding solution, we introduce (1) a novel precoder codebook design that lends itself to precoder interpolation, across subcarriers, followed by mode selection, (2) a new precoder interpolator and, finally, (3) a clustered mode selection approach that significantly reduces the feedback overhead related to the mode information on each subcarrier. Monte-Carlo bit-error rate (BER) performance simulations demonstrate the effectiveness of the proposed quantized multi-mode precoding solution, at reasonable feedback overhead

Multimode basis selection for spatial multiplexing with limited feedback

Proposed is multimode basis selection in which the active bases are selected at the receiver from the common unitary basis set known at both receiving and transmitting ends, conveyed to the transmitter using limited feedback, and assembled into a precoding matrix at the transmitter. It is shown that the proposed multimode basis selection scheme outperforms both multimode antenna selection and Grassmannian multimode precoding in capacity in correlated fading channels without additional complexity and feedback.

Multimode precoding for MIMO wireless systems

Multiple-input multiple-output (MIMO) wireless systems obtain large diversity and capacity gains by employing multielement antenna arrays at both the transmitter and receiver. The theoretical performance benefits of MIMO systems, however, are irrelevant unless low error rate, spectrally efficient signaling techniques are found. This paper proposes a new method for designing high data-rate spatial signals with low error rates. The basic idea is to use transmitter channel information to adaptively vary the transmission scheme for a fixed data rate. This adaptation is done by varying the number of substreams and the rate of each substream in a precoded spatial multiplexing system. We show that these substreams can be designed to obtain full diversity and full rate gain using feedback from the receiver to transmitter. We model the feedback using a limited feedback scenario where only finite sets, or codebooks, of possible precoding configurations are known to both the transmitter and receiver. Monte Carlo simulations show substantial performance gains over beamforming and spatial multiplexing.