204 research outputs found
Filter and nested-lattice code design for fading MIMO channels with side-information
Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for
channels with interference known only at the transmitter, where the known
interference is treated as side-information (SI). As a special case of LA-GPC,
dirty paper coding has been shown to be able to achieve the optimal
interference-free rate for interference channels with perfect channel state
information at the transmitter (CSIT). In the cases where only the channel
distribution information at the transmitter (CDIT) is available, LA-GPC also
has good (sometimes optimal) performance in a variety of fast and slow fading
SI channels. In this paper, we design the filters in nested-lattice based
coding to make it achieve the same rate performance as LA-GPC in multiple-input
multiple-output (MIMO) channels. Compared with the random Gaussian codebooks
used in previous works, our resultant coding schemes have an algebraic
structure and can be implemented in practical systems. A simulation in a
slow-fading channel is also provided, and near interference-free error
performance is obtained. The proposed coding schemes can serve as the
fundamental building blocks to achieve the promised rate performance of MIMO
Gaussian broadcast channels with CDIT or perfect CSITComment: submitted to IEEE Transactions on Communications, Feb, 200
AMMSE Optimization for Multiuser MISO Systems with Imperfect CSIT and Perfect CSIR
In this paper, we consider the design of robust linear precoders for MU-MISO
systems where users have perfect Channel State Information (CSI) while the BS
has partial CSI. In particular, the BS has access to imperfect estimates of the
channel vectors, in addition to the covariance matrices of the estimation error
vectors. A closed-form expression for the Average Minimum Mean Square Error
(AMMSE) is obtained using the second order Taylor Expansion. This approximation
is used to formulate two fairness-based robust design problems: a maximum
AMMSE-constrained problem and a power-constrained problem. We propose an
algorithm based on convex optimization techniques to address the first problem,
while the second problem is tackled by exploiting the close relationship
between the two problems, in addition to their monotonic natures.Comment: IEEE Global Communications Conference (GLOBECOM) 201
Codebook Based Hybrid Precoding for Millimeter Wave Multiuser Systems
In millimeter wave (mmWave) systems, antenna architecture limitations make it
difficult to apply conventional fully digital precoding techniques but call for
low cost analog radio-frequency (RF) and digital baseband hybrid precoding
methods. This paper investigates joint RF-baseband hybrid precoding for the
downlink of multiuser multi-antenna mmWave systems with a limited number of RF
chains. Two performance measures, maximizing the spectral efficiency and the
energy efficiency of the system, are considered. We propose a codebook based RF
precoding design and obtain the channel state information via a beam sweep
procedure. Via the codebook based design, the original system is transformed
into a virtual multiuser downlink system with the RF chain constraint.
Consequently, we are able to simplify the complicated hybrid precoding
optimization problems to joint codeword selection and precoder design (JWSPD)
problems. Then, we propose efficient methods to address the JWSPD problems and
jointly optimize the RF and baseband precoders under the two performance
measures. Finally, extensive numerical results are provided to validate the
effectiveness of the proposed hybrid precoders.Comment: 35 pages, 9 figures, to appear in Trans. on Signal Process, 201
The DoF of Network MIMO with Backhaul Delays
We consider the problem of downlink precoding for Network (multi-cell) MIMO
networks where Transmitters (TXs) are provided with imperfect Channel State
Information (CSI). Specifically, each TX receives a delayed channel estimate
with the delay being specific to each channel component. This model is
particularly adapted to the scenarios where a user feeds back its CSI to its
serving base only as it is envisioned in future LTE networks. We analyze the
impact of the delay during the backhaul-based CSI exchange on the rate
performance achieved by Network MIMO. We highlight how delay can dramatically
degrade system performance if existing precoding methods are to be used. We
propose an alternative robust beamforming strategy which achieves the maximal
performance, in DoF sense. We verify by simulations that the theoretical DoF
improvement translates into a performance increase at finite Signal-to-Noise
Ratio (SNR) as well
Novel transmission and beamforming strategies for multiuser MIMO with various CSIT types
In multiuser multi-antenna wireless systems, the transmission and beamforming strategies that achieve the sum rate capacity depend critically on the acquisition of perfect Channel State Information at the Transmitter (CSIT).
Accordingly, a high-rate low-latency feedback link between the receiver and the transmitter is required to keep the latter accurately and instantaneously informed about the CSI.
In realistic wireless systems, however, only imperfect CSIT is achievable due to pilot contamination, estimation error, limited feedback and delay, etc.
As an intermediate solution, this thesis investigates novel transmission strategies suitable for various imperfect CSIT scenarios and the associated beamforming techniques to optimise the rate performance.
First, we consider a two-user Multiple-Input-Single-Output (MISO) Broadcast Channel (BC) under statistical and delayed CSIT.
We mainly focus on linear beamforming and power allocation designs for ergodic sum rate maximisation.
The proposed designs enable higher sum rate than the conventional designs.
Interestingly, we propose a novel transmission framework which makes better use of statistical and delayed CSIT and smoothly bridges between statistical CSIT-based strategies and delayed CSIT-based strategies.
Second, we consider a multiuser massive MIMO system under partial and statistical CSIT.
In order to tackle multiuser interference incurred by partial CSIT, a Rate-Splitting (RS) transmission strategy has been proposed recently.
We generalise the idea of RS into the large-scale array.
By further exploiting statistical CSIT, we propose a novel framework Hierarchical-Rate-Splitting that is particularly suited to massive MIMO systems.
Third, we consider a multiuser Millimetre Wave (mmWave) system with hybrid analog/digital precoding under statistical and quantised CSIT.
We leverage statistical CSIT to design digital precoder for interference mitigation while all feedback overhead is reserved for precise analog beamforming.
For very limited feedback and/or very sparse channels, the proposed precoding scheme yields higher sum rate than the conventional precoding schemes under a fixed total feedback constraint.
Moreover, a RS transmission strategy is introduced to further tackle the multiuser interference, enabling remarkable saving in feedback overhead compared with conventional transmission strategies.
Finally, we investigate the downlink hybrid precoding for physical layer multicasting with a limited number of RF chains.
We propose a low complexity algorithm to compute the analog precoder that achieves near-optimal max-min performance.
Moreover, we derive a simple condition under which the hybrid precoding driven by a limited number of RF chains incurs no loss of optimality with respect to the fully digital precoding case.Open Acces
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