68 research outputs found
A limited feedback scheme based on spatially correlated channels for coordinated multipoint systems
High spectral efficiency can be achieved in the downlink of multi-antenna coordinated multi-point systems provided that the multiuser interference is appropriately managed at the transmitter side. For this sake, downlink channel information needs to be sent back by the users, thus reducing the rate available at the uplink channel. The amount and type of feedback information required has been extensively studied and many limited feedback schemes have been proposed lately. A common pattern to all of them is that achieving low rates of feedback information is possible at the cost of increasing complexity at the user side and, sometimes, assuming that some statistics of the channel are known. In this article, we propose a simple and versatile limited feedback scheme that exploits the spatial correlation at each multi-antenna base station (BS) without requiring any previous statistical information of the channel and without adding significant computational complexity. It is based on the separate quantization of the channel impulse response modulus and phase and it shows better mean square error performance than the standard scheme based on quantization of real and imaginary parts. In order to evaluate the performance of the downlink regarding multiuser interference management, different precoding techniques at the BSs, such as zero-forcing (ZF), Tomlinson-Harashima precoding (THP) and lattice reduction Tomlinson- Harashima precoding (LRTHP), have been evaluated. Simulations results show that LRTHP and THP present a higher robustness than ZF precoding against channel quantization errors but at the cost of a higher complexity at the BS. Regarding sum-capacity and bit error rate performances, our versatile scheme achieves better results than the standard one in the medium and high SNR regime, that is, in the region where quantization errors are dominant against noise, for the same feedback cost measured in bits per user
Novel Efficient Precoding Techniques for Multiuser MIMO Systems
In Multiuser MIMO (MU-MIMO) systems, precoding is essential to eliminate or minimize the multiuser interference (MUI).
However, the design of a suitable precoding algorithm with good overall
performance and low computational complexity at the same time is quite challenging, especially with the increase of system dimensions.
In this thesis, we explore the art of novel low-complexity high-performance precoding algorithms with both linear and non-linear processing strategies.
Block diagonalization (BD)-type based precoding techniques are well-known linear precoding strategies
for MU-MIMO systems.
By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed
into multiple independent parallel SU-MIMO channels and achieves the
maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from
two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix.
In this thesis, two categories of low-complexity precoding algorithms are proposed to
reduce the computational complexity and improve the performance of BD-type precoding algorithms.
One is based on multiple LQ decompositions and lattice reductions. The other one is based on a channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels.
Both of the two proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error
rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity.
Tomlinson-Harashima precoding (THP) is a prominent nonlinear processing technique employed at the transmit side and is a dual to the successive interference cancelation (SIC) detection at the receive side. Like SIC detection, the performance of THP strongly depends on the ordering of the precoded symbols.
The optimal ordering algorithm, however, is impractical for MU-MIMO systems with multiple receive antennas. We propose a multi-branch THP (MB-THP) scheme and algorithms that employ multiple transmit processing and ordering strategies along with a selection scheme to mitigate interference in MU-MIMO systems.
Two types of multi-branch THP (MB-THP) structures are proposed. The first one employs a decentralized strategy with diagonal weighted filters at the receivers of the users and the second uses a diagonal weighted filter at the transmitter.
The MB-MMSE-THP algorithms are also derived based on an extended system model with the aid of an LQ decomposition, which is much simpler compared to the conventional MMSE-THP algorithms. Simulation results show that a better BER performance can be achieved by the proposed MB-MMSE-THP precoder with a small computational complexity increase
Capacity Enhancement of Multiuser Wireless Communication System through Adaptive Non-Linear Pre coding
Multiuser multiple-input multiple-output (MIMO) nonlinear pre coding techniques face the issue of poor computational scalability of the size of the network. But by this nonlinear pre coding technique the interference is pre-cancelled automatically and also provides better capacity. So in order to reduce the computational burden in this paper, a definitive issue of MU-MIMO scalability is tackled through a non-linear adaptive optimum vector perturbation technique. Unlike the conventional (Vector Perturbation) VP methods, here a novel anterograde tracing is utilized which is usually recognized in the nervous system thus reducing complexity. The tracing of distance can be done through an iterative-optimization procedure. By this novel non-linear technique the capacity is improved to a greater extend which is explained practically. By means of this, the computational complexity is managed to be in the cubic order of the size of MUMIMO, and this mainly derives from the inverse of the channel matrix. The proposed signal processing system has been implemented in the working platform of MATLAB/SIMULINK. The simulation results of proposed communication system and comparison with existing systems shows the significance of the proposed work
Implementation of Tomlinson Harashima Recorder(THP) in Cloud Radio Access Networks (CRANs)
The evolution of cellular communication networks from 1G through 4G has resulted in a steady increase in the allowable rates for users (UEs). However, other cell interference (OCI) still remains the performance limiting factor. OCI is the interference from signals received from other cells. Mitigation of OCI using interference cancellation strategies results in improvement
of allowable rates. This can be achieved by Cloud radio access networks (C-RANs), which is also labeled as network multiple-input-multiple-output (MIMO) centralized precoding architecture in literature.Precoders in CRANs are designed to presubtract the known interference at the transmitter. It basically exploits transmit diversity by weighting information stream, i.e. the transmitter send the coded information to the receiver in accordance with the pre-knowledge of the channel. A nonlinear precoder named THP precoder is implemented in my project work
PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink
We investigate an orthogonal frequency-division multiplexing (OFDM)-based
downlink transmission scheme for large-scale multi-user (MU) multiple-input
multiple-output (MIMO) wireless systems. The use of OFDM causes a high
peak-to-average (power) ratio (PAR), which necessitates expensive and
power-inefficient radio-frequency (RF) components at the base station. In this
paper, we present a novel downlink transmission scheme, which exploits the
massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems to
achieve low PAR. Specifically, we propose to jointly perform MU precoding, OFDM
modulation, and PAR reduction by solving a convex optimization problem. We
develop a corresponding fast iterative truncation algorithm (FITRA) and show
numerical results to demonstrate tremendous PAR-reduction capabilities. The
significantly reduced linearity requirements eventually enable the use of
low-cost RF components for the large-scale MU-MIMO-OFDM downlink.Comment: To appear in IEEE Journal on Selected Areas in Communication
Multi-Antenna Techniques for Next Generation Cellular Communications
Future cellular communications are expected to offer substantial improvements for the pre- existing mobile services with higher data rates and lower latency as well as pioneer new types of applications that must comply with strict demands from a wider range of user types. All of these tasks require utmost efficiency in the use of spectral resources. Deploying multiple antennas introduces an additional signal dimension to wireless data transmissions, which provides a significant alternative solution against the plateauing capacity issue of the limited available spectrum. Multi-antenna techniques and the associated key enabling technologies possess unquestionable potential to play a key role in the evolution of next generation cellular systems.
Spectral efficiency can be improved on downlink by concurrently serving multiple users with high-rate data connections on shared resources. In this thesis optimized multi-user multi-input multi-output (MIMO) transmissions are investigated on downlink from both filter design and resource allocation/assignment points of view. Regarding filter design, a joint baseband processing method is proposed specifically for high signal-to-noise ratio (SNR) conditions, where the necessary signaling overhead can be compensated for. Regarding resource scheduling, greedy- and genetic-based algorithms are proposed that demand lower complexity with large number of resource blocks relative to prior implementations.
Channel estimation techniques are investigated for massive MIMO technology. In case of channel reciprocity, this thesis proposes an overhead reduction scheme for the signaling of user channel state information (CSI) feedback during a relative antenna calibration. In addition, a multi-cell coordination method is proposed for subspace-based blind estimators on uplink, which can be implicitly translated to downlink CSI in the presence of ideal reciprocity. Regarding non-reciprocal channels, a novel estimation technique is proposed based on reconstructing full downlink CSI from a select number of dominant propagation paths. The proposed method offers drastic compressions in user feedback reports and requires much simpler downlink training processes.
Full-duplex technology can provide up to twice the spectral efficiency of conventional resource divisions. This thesis considers a full-duplex two-hop link with a MIMO relay and investigates mitigation techniques against the inherent loop-interference. Spatial-domain suppression schemes are developed for the optimization of full-duplex MIMO relaying in a coverage extension scenario on downlink. The proposed methods are demonstrated to generate data rates that closely approximate their global bounds
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