25 research outputs found
Precoder design for space-time coded systems over correlated Rayleigh fading channels using convex optimization
A class of computationally efficient linear precoders for space-time block coded multiple-input multiple-output wireless systems is derived based on the minimization of the exact symbol error rate (SER) and its upper bound. Both correlations at the transmitter and receiver are assumed to be present, and only statistical channel state information in the form of the transmit and receive correlation matrices is assumed to be available at the transmitter. The convexity of the design based on SER minimization is established and exploited. The advantage of the developed technique is its low complexity. We also find various relationships of the proposed designs to the existing precoding techniques, and derive very simple closed-form precoders for special cases such as two or three receive antennas and constant receive correlation. The numerical simulations illustrate the excellent SER performance of the proposed precoders
Performance of a non-orthogonal STBC over correlative fading channels
[[abstract]]It has been recently shown that, for non-orthogonal space-time block code (STBC), the multiple-input multiple-output (MIMO) maximum-likelihood (ML) metric can also be decoupled into single-input single-output (SISO) ML metrics for decoding simplification just as for orthogonal STBC. In this work, we utilized the decoupled metrics of a non-orthogonal STBC to derive the symbol error rate (SER) in correlative fading channels and show that, when the non-orthogonal code is generated by converting an orthogonal code using proper precoding, the conversion will improve the SER performance when the MIMO channels are correlated.[[conferencetype]]國際[[conferencedate]]20080604~20080606[[booktype]]紙本[[conferencelocation]]Hoi an, Vietna
Optimized Compressed Sensing Matrix Design for Noisy Communication Channels
We investigate a power-constrained sensing matrix design problem for a
compressed sensing framework. We adopt a mean square error (MSE) performance
criterion for sparse source reconstruction in a system where the
source-to-sensor channel and the sensor-to-decoder communication channel are
noisy. Our proposed sensing matrix design procedure relies upon minimizing a
lower-bound on the MSE. Under certain conditions, we derive closed-form
solutions to the optimization problem. Through numerical experiments, by
applying practical sparse reconstruction algorithms, we show the strength of
the proposed scheme by comparing it with other relevant methods. We discuss the
computational complexity of our design method, and develop an equivalent
stochastic optimization method to the problem of interest that can be solved
approximately with a significantly less computational burden. We illustrate
that the low-complexity method still outperforms the popular competing methods.Comment: Submitted to IEEE ICC 2015 (EXTENDED VERSION
상향링크 셀룰러 시스템에서 채널 상관 기반의 협력 사용자 스케줄링 기법
In this paper, we consider multi-user scheduling to avoid other cell interference (OCI) in the uplink of
cellular systems. The base station (BS) determines a user group that can minimize the interference from other
cells by exploiting the spatial correlation matrix of users from adjacent BSs. The proposed scheme is
applicable to multi-input multi-output (MIMO) as well as single-input multi-output (SIMO) environments by
applying an eigen-beamforming technique, enabling the use of flexible antenna structures at the transmitter.
Simulation results show that the proposed multi-cell scheduling significantly increase the ergodic capacity by
avoiding the OCI compared to conventional scheduling schemes, particularly in high mobility and highly
correlated channel environments.Seoul R&BD Progra
General Rank Multiuser Downlink Beamforming With Shaping Constraints Using Real-valued OSTBC
In this paper we consider optimal multiuser downlink beamforming in the
presence of a massive number of arbitrary quadratic shaping constraints. We
combine beamforming with full-rate high dimensional real-valued orthogonal
space time block coding (OSTBC) to increase the number of beamforming weight
vectors and associated degrees of freedom in the beamformer design. The
original multi-constraint beamforming problem is converted into a convex
optimization problem using semidefinite relaxation (SDR) which can be solved
efficiently. In contrast to conventional (rank-one) beamforming approaches in
which an optimal beamforming solution can be obtained only when the SDR
solution (after rank reduction) exhibits the rank-one property, in our approach
optimality is guaranteed when a rank of eight is not exceeded. We show that our
approach can incorporate up to 79 additional shaping constraints for which an
optimal beamforming solution is guaranteed as compared to a maximum of two
additional constraints that bound the conventional rank-one downlink
beamforming designs. Simulation results demonstrate the flexibility of our
proposed beamformer design
Rank-Two Beamforming and Power Allocation in Multicasting Relay Networks
In this paper, we propose a novel single-group multicasting relay beamforming
scheme. We assume a source that transmits common messages via multiple
amplify-and-forward relays to multiple destinations. To increase the number of
degrees of freedom in the beamforming design, the relays process two received
signals jointly and transmit the Alamouti space-time block code over two
different beams. Furthermore, in contrast to the existing relay multicasting
scheme of the literature, we take into account the direct links from the source
to the destinations. We aim to maximize the lowest received quality-of-service
by choosing the proper relay weights and the ideal distribution of the power
resources in the network. To solve the corresponding optimization problem, we
propose an iterative algorithm which solves sequences of convex approximations
of the original non-convex optimization problem. Simulation results demonstrate
significant performance improvements of the proposed methods as compared with
the existing relay multicasting scheme of the literature and an algorithm based
on the popular semidefinite relaxation technique
Beamforming Optimization for Full-Duplex Wireless-powered MIMO Systems
We propose techniques for optimizing transmit beamforming in a full-duplex
multiple-input-multiple-output (MIMO) wireless-powered communication system,
which consists of two phases. In the first phase, the wireless-powered mobile
station (MS) harvests energy using signals from the base station (BS), whereas
in the second phase, both MS and BS communicate to each other in a full-duplex
mode. When complete instantaneous channel state information (CSI) is available,
the BS beamformer and the time-splitting (TS) parameter of energy harvesting
are jointly optimized in order to obtain the BS-MS rate region. The joint
optimization problem is non-convex, however, a computationally efficient
optimum technique, based upon semidefinite relaxation and line-search, is
proposed to solve the problem. A sub-optimum zero-forcing approach is also
proposed, in which a closed-form solution of TS parameter is obtained. When
only second-order statistics of transmit CSI is available, we propose to
maximize the ergodic information rate at the MS, while maintaining the outage
probability at the BS below a certain threshold. An upper bound for the outage
probability is also derived and an approximate convex optimization framework is
proposed for efficiently solving the underlying non-convex problem. Simulations
demonstrate the advantages of the proposed methods over the sub-optimum and
half-duplex ones.Comment: 14 pages, accepte