91 research outputs found
AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing
The enormous success of advanced wireless devices is pushing the demand for
higher wireless data rates. Denser spectrum reuse through the deployment of
more access points per square mile has the potential to successfully meet the
increasing demand for more bandwidth. In theory, the best approach to density
increase is via distributed multiuser MIMO, where several access points are
connected to a central server and operate as a large distributed multi-antenna
access point, ensuring that all transmitted signal power serves the purpose of
data transmission, rather than creating "interference." In practice, while
enterprise networks offer a natural setup in which distributed MIMO might be
possible, there are serious implementation difficulties, the primary one being
the need to eliminate phase and timing offsets between the jointly coordinated
access points.
In this paper we propose AirSync, a novel scheme which provides not only time
but also phase synchronization, thus enabling distributed MIMO with full
spatial multiplexing gains. AirSync locks the phase of all access points using
a common reference broadcasted over the air in conjunction with a Kalman filter
which closely tracks the phase drift. We have implemented AirSync as a digital
circuit in the FPGA of the WARP radio platform. Our experimental testbed,
comprised of two access points and two clients, shows that AirSync is able to
achieve phase synchronization within a few degrees, and allows the system to
nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC
and higher layer aspects of a practical deployment. To the best of our
knowledge, AirSync offers the first ever realization of the full multiuser MIMO
gain, namely the ability to increase the number of wireless clients linearly
with the number of jointly coordinated access points, without reducing the per
client rate.Comment: Submitted to Transactions on Networkin
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
Resource Allocation for Power Minimization in the Downlink of THP-based Spatial Multiplexing MIMO-OFDMA Systems
In this work, we deal with resource allocation in the downlink of spatial
multiplexing MIMO-OFDMA systems. In particular, we concentrate on the problem
of jointly optimizing the transmit and receive processing matrices, the channel
assignment and the power allocation with the objective of minimizing the total
power consumption while satisfying different quality-of-service requirements. A
layered architecture is used in which users are first partitioned in different
groups on the basis of their channel quality and then channel assignment and
transceiver design are sequentially addressed starting from the group of users
with most adverse channel conditions. The multi-user interference among users
belonging to different groups is removed at the base station using a
Tomlinson-Harashima pre-coder operating at user level. Numerical results are
used to highlight the effectiveness of the proposed solution and to make
comparisons with existing alternatives.Comment: 12 pages, 6 figures, IEEE Trans. Veh. Techno
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
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