On channel quantization and feedback strategies for multiuser MIMO-OFDM downlink systems (original) (raw)
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Channel Quantization and Feedback Optimization in Multiuser MIMO-OFDM Downlink Systems
IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference, 2008
We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. The paper has two main contributions: firstly we show conditions on the coherence bandwidth of the channel and the FB rate per RB that allow for a simpler characterization of the RB channel matrix by a space vector, causing negligible performance loss. This is accomplished after deriving a new performance metric for RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.
Vector Quantization of Channel Information in Linear Multi-User MIMO Systems
2006 IEEE Ninth International Symposium on Spread Spectrum Techniques and Applications, 2006
In this paper, we propose a new vector quantization (VQ) algorithm for encoding channel state information feedback in multiple antenna, multiuser systems operating on flat fading channels with rich scattering. We consider an approach where the receiver chooses an instantaneous throughput maximizing modulation matrix from a finite set of predefined matrices (codewords). The codebook of modulation matrices is constructed based on joint optimization of the dominant channel eigenmodes of users and separate quantization of power levels. The proposed algorithm is very flexible and can be used in a variety of system configurations, including varying number of receiver antennas and frequency selective channels. We implement the proposed algorithm on flat fading MIMO channels and show the influence of the feedback rate on system capacity. We demonstrate that, even with low feedback rate, the ergodic capacity of the proposed system closely approaches the theoretic capacity of the system with perfect channel state information at the transmitter.
Joint low-rate feedback and channel quantization for the MIMO broadcast channel
AFRICON 2007, 2007
For the downlink of a wireless cellular system where the base station (BS) uses multiple antennas in a beamforming configuration for a multiuser transmission (broadcasting), we investigate two techniques for quantizing the channel state information at the mobile terminal and feeding it back to the BS. In both cases quantization of channel vectors and feedback signaling are jointly designed in order to obtain a low-rate feedback (FB). In particular, we first consider a tree structure vector quantizer (VQ) of the channel vector with a novel metric, as an alternative to the classical mean square error. It is seen that the tree search allows to lower the FB signaling rate also in a time-varying environment. As an alternative, a predictive VQ is proposed. These two and other FB strategies were extensively compared in a typical cellular environment for different mobile speeds and FB rates.
Feedback schemes for multiuser MIMO-OFDM downlink
2008
Abstract We consider a MIMO-OFDM broadcast channel and compare achievable ergodic rates under three channel state feedback schemes: analog feedback, direction quantized feedback and ldquotime-domainrdquo channel quantized feedback. The third scheme is new, and it is inspired by rate-distortion theory of Gaussian correlated sources. For each scheme we derive the conditions under which the system achieves full multiplexing gain.
Quantization Techniques in Linearly Precoded Multiuser MIMO System with Limited Feedback
Multi-user wireless systems with multiple antennas can drastically increase the capac- ity while maintaining the quality of service requirements. The best performance of these systems is obtained at the presence of instantaneous channel knowledge. Since uplink- downlink channel reciprocity does not hold in frequency division duplex and broadband time division duplex systems, efficient channel quantization becomes important. This thesis focuses on different quantization techniques in a linearly precoded multi-user wire- less system. Our work provides three major contributions. First, we come up with an end-to-end transceiver design, incorporating precoder, receive combining and feedback policy, that works well at low feedback overhead. Second, we provide optimal bit allocation across the gain and shape of a complex vector to reduce the quantization error and investigate its effect in the multiuser wireless system. Third, we design an adaptive differential quantizer that reduces feedback overhead by utilizing temporal correlation of the channels in a time varying scenario.
Efficient channel quantization scheme for multi-user MIMO broadcast channels with RBD precoding
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008
Regularized block diagonalization (RBD) is a new linear precoding technique for the multi-antenna broadcast channel and has a significantly improved sum rate and diversity order compared to all previously proposed linear precoding techniques. We consider a limited feedback system with RBD precoding, in which each receiver has perfect channel state information (CSI) and quantizes its channel. The transmitter receives the quantized CSI with a finite number of feedback bits from each receiver. In contrast to zeroforcing (ZF) or block diagonalization (BD) precoding, where the transmitter only requires the channel direction information which refers to the knowledge of subspaces spanned by the users' channel matrices, for RBD precoding the transmitter additionally requires the channel magnitude information which defines the strength of the eigenmodes of the users' channel matrices. The key contribution of our work is that we propose a new scheme for the channel quantization to supply the transmitter with both channel direction and magnitude information. Based on this new scheme, firstly, we investigate a random vector quantization (RVQ). We derive a bound for the throughput loss due to imperfect CSI and find a way to achieve the bound by linearly increasing the number of feedback bits with the system SNR. Secondly, we modify the LBG vector quantization algorithm to obtain a dominant eigenvector based LBG (DE-LBG) vector quantization which can significantly reduce the number of feedback bits compared to RVQ. Finally, we demonstrate that the DE-LBG vector quantization can be applied to an OFDM-based multi-user MIMO system.
Efficient Quantization for Feedback in MIMO Broadcasting Systems
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006
We consider the problem of joint multiplexer-scheduler design for transmitting independent data streams over a Gaussian multiple-antenna broadcast channel in which feedback is used to convey channel state information from receivers to the transmitter. It is known that various low complexity strategies can achieve the optimal rate scaling as a function of receiver population size. In this work we develop a simple and efficient quantization strategy for use on the feedback link of such architectures.
Multiuser Diversity - Multiplexing Tradeoff in MIMO Broadcast Channels with Limited Feedback
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006
We consider joint scheduling and beamforming in a broadcast channel with multiple antennas at the transmitter and a single antenna at the mobile receiver. Perfect channel knowledge is assumed to be available at the receiver while the transmitter is provided with partial channel state information (CSIT) through a limited rate feedback channel. Each user feeds back quantized information regarding the channel vector direction (from a codebook) and a quantized (scalar) channel quality indicator. We identify the tradeoff between multiuser diversity and spatial multiplexing gain given a limited amount of feedback bits. Scaling laws of the above parameters are derived in order to achieve a target rate performance. Our results reveal useful design guidelines for the split of feedback bits for channel quantization and channel quality.
Multiuser MIMO achievable rates with downlink training and channel state feedback
2010
Abstract In this paper, we consider a multiple-input-multiple-output (MIMO) fading broadcast channel and compute achievable ergodic rates when channel state information (CSI) is acquired at the receivers via downlink training and it is provided to the transmitter by channel state feedback. Unquantized (analog) and quantized (digital) channel state feedback schemes are analyzed and compared under various assumptions.
2007
Abstract We consider a MIMO fading broadcast channel and compute achievable ergodic rates when channel state information is acquired at the receivers via downlink training and explicit channel feedback is performed to provide transmitter channel state information (CSIT). Both “analog” and quantized (digital) channel feedback are analyzed, and digital feedback is shown to be potentially superior when the feedback channel uses per channel coefficient is larger than 1.