1,183 research outputs found
Linear Precoding in Cooperative MIMO Cellular Networks with Limited Coordination Clusters
In a cooperative multiple-antenna downlink cellular network, maximization of
a concave function of user rates is considered. A new linear precoding
technique called soft interference nulling (SIN) is proposed, which performs at
least as well as zero-forcing (ZF) beamforming. All base stations share channel
state information, but each user's message is only routed to those that
participate in the user's coordination cluster. SIN precoding is particularly
useful when clusters of limited sizes overlap in the network, in which case
traditional techniques such as dirty paper coding or ZF do not directly apply.
The SIN precoder is computed by solving a sequence of convex optimization
problems. SIN under partial network coordination can outperform ZF under full
network coordination at moderate SNRs. Under overlapping coordination clusters,
SIN precoding achieves considerably higher throughput compared to myopic ZF,
especially when the clusters are large.Comment: 13 pages, 5 figure
Robust Lattice Alignment for K-user MIMO Interference Channels with Imperfect Channel Knowledge
In this paper, we consider a robust lattice alignment design for K-user
quasi-static MIMO interference channels with imperfect channel knowledge. With
random Gaussian inputs, the conventional interference alignment (IA) method has
the feasibility problem when the channel is quasi-static. On the other hand,
structured lattices can create structured interference as opposed to the random
interference caused by random Gaussian symbols. The structured interference
space can be exploited to transmit the desired signals over the gaps. However,
the existing alignment methods on the lattice codes for quasi-static channels
either require infinite SNR or symmetric interference channel coefficients.
Furthermore, perfect channel state information (CSI) is required for these
alignment methods, which is difficult to achieve in practice. In this paper, we
propose a robust lattice alignment method for quasi-static MIMO interference
channels with imperfect CSI at all SNR regimes, and a two-stage decoding
algorithm to decode the desired signal from the structured interference space.
We derive the achievable data rate based on the proposed robust lattice
alignment method, where the design of the precoders, decorrelators, scaling
coefficients and interference quantization coefficients is jointly formulated
as a mixed integer and continuous optimization problem. The effect of imperfect
CSI is also accommodated in the optimization formulation, and hence the derived
solution is robust to imperfect CSI. We also design a low complex iterative
optimization algorithm for our robust lattice alignment method by using the
existing iterative IA algorithm that was designed for the conventional IA
method. Numerical results verify the advantages of the proposed robust lattice
alignment method
Seeing the Unobservable: Channel Learning for Wireless Communication Networks
Wireless communication networks rely heavily on channel state information
(CSI) to make informed decision for signal processing and network operations.
However, the traditional CSI acquisition methods is facing many difficulties:
pilot-aided channel training consumes a great deal of channel resources and
reduces the opportunities for energy saving, while location-aided channel
estimation suffers from inaccurate and insufficient location information. In
this paper, we propose a novel channel learning framework, which can tackle
these difficulties by inferring unobservable CSI from the observable one. We
formulate this framework theoretically and illustrate a special case in which
the learnability of the unobservable CSI can be guaranteed. Possible
applications of channel learning are then described, including cell selection
in multi-tier networks, device discovery for device-to-device (D2D)
communications, as well as end-to-end user association for load balancing. We
also propose a neuron-network-based algorithm for the cell selection problem in
multi-tier networks. The performance of this algorithm is evaluated using
geometry-based stochastic channel model (GSCM). In settings with 5 small cells,
the average cell-selection accuracy is 73% - only a 3.9% loss compared with a
location-aided algorithm which requires genuine location information.Comment: 6 pages, 4 figures, accepted by GlobeCom'1
Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
This article provides an overview of the state-of-art results on
communication resource allocation over space, time, and frequency for emerging
cognitive radio (CR) wireless networks. Focusing on the
interference-power/interference-temperature (IT) constraint approach for CRs to
protect primary radio transmissions, many new and challenging problems
regarding the design of CR systems are formulated, and some of the
corresponding solutions are shown to be obtainable by restructuring some
classic results known for traditional (non-CR) wireless networks. It is
demonstrated that convex optimization plays an essential role in solving these
problems, in a both rigorous and efficient way. Promising research directions
on interference management for CR and other related multiuser communication
systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex
optimization for signal processin
Using Channel Output Feedback to Increase Throughput in Hybrid-ARQ
Hybrid-ARQ protocols have become common in many packet transmission systems
due to their incorporation in various standards. Hybrid-ARQ combines the normal
automatic repeat request (ARQ) method with error correction codes to increase
reliability and throughput. In this paper, we look at improving upon this
performance using feedback information from the receiver, in particular, using
a powerful forward error correction (FEC) code in conjunction with a proposed
linear feedback code for the Rayleigh block fading channels. The new hybrid-ARQ
scheme is initially developed for full received packet feedback in a
point-to-point link. It is then extended to various different multiple-antenna
scenarios (MISO/MIMO) with varying amounts of packet feedback information.
Simulations illustrate gains in throughput.Comment: 30 page
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