94 research outputs found
Robust Sum MSE Optimization for Downlink Multiuser MIMO Systems with Arbitrary Power Constraint: Generalized Duality Approach
This paper considers linear minimum meansquare- error (MMSE) transceiver
design problems for downlink multiuser multiple-input multiple-output (MIMO)
systems where imperfect channel state information is available at the base
station (BS) and mobile stations (MSs). We examine robust sum mean-square-error
(MSE) minimization problems. The problems are examined for the generalized
scenario where the power constraint is per BS, per BS antenna, per user or per
symbol, and the noise vector of each MS is a zero-mean circularly symmetric
complex Gaussian random variable with arbitrary covariance matrix. For each of
these problems, we propose a novel duality based iterative solution. Each of
these problems is solved as follows. First, we establish a novel sum average
meansquare- error (AMSE) duality. Second, we formulate the power allocation
part of the problem in the downlink channel as a Geometric Program (GP). Third,
using the duality result and the solution of GP, we utilize alternating
optimization technique to solve the original downlink problem. To solve robust
sum MSE minimization constrained with per BS antenna and per BS power problems,
we have established novel downlink-uplink duality. On the other hand, to solve
robust sum MSE minimization constrained with per user and per symbol power
problems, we have established novel downlink-interference duality. For the
total BS power constrained robust sum MSE minimization problem, the current
duality is established by modifying the constraint function of the dual uplink
channel problem. And, for the robust sum MSE minimization with per BS antenna
and per user (symbol) power constraint problems, our duality are established by
formulating the noise covariance matrices of the uplink and interference
channels as fixed point functions, respectively.Comment: IEEE TSP Journa
Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader
Backscatter communication (BSC) is being realized as the core technology for
pervasive sustainable Internet-of-Things applications. However, owing to the
resource-limitations of passive tags, the efficient usage of multiple antennas
at the reader is essential for both downlink excitation and uplink detection.
This work targets at maximizing the achievable sum-backscattered-throughput by
jointly optimizing the transceiver (TRX) design at the reader and
backscattering coefficients (BC) at the tags. Since, this joint problem is
nonconvex, we first present individually-optimal designs for the TRX and BC. We
show that with precoder and {combiner} designs at the reader respectively
targeting downlink energy beamforming and uplink Wiener filtering operations,
the BC optimization at tags can be reduced to a binary power control problem.
Next, the asymptotically-optimal joint-TRX-BC designs are proposed for both low
and high signal-to-noise-ratio regimes. Based on these developments, an
iterative low-complexity algorithm is proposed to yield an efficient
jointly-suboptimal design. Thereafter, we discuss the practical utility of the
proposed designs to other application settings like wireless powered
communication networks and BSC with imperfect channel state information.
Lastly, selected numerical results, validating the analysis and shedding novel
insights, demonstrate that the proposed designs can yield significant
enhancement in the sum-backscattered throughput over existing benchmarks.Comment: 17 pages, 5 figures, accepted for publication in IEEE Transactions on
Communication
Recent Advances in Acquiring Channel State Information in Cellular MIMO Systems
In cellular multi-user multiple input multiple output (MU-MIMO) systems the quality of the available channel state information (CSI) has a large impact on the system performance. Specifically, reliable CSI at the transmitter is required to determine the appropriate modulation and coding scheme, transmit power and the precoder vector, while CSI at the receiver is needed to decode the received data symbols. Therefore, cellular MUMIMO systems employ predefined pilot sequences and configure associated time, frequency, code and power resources to facilitate the acquisition of high quality CSI for data transmission and reception. Although the trade-off between the resources used user data transmission has been known for long, the near-optimal configuration of the vailable system resources for pilot and data transmission is a topic of current research efforts. Indeed, since the fifth generation of cellular systems utilizes heterogeneous networks in which base stations are equipped with a large number of transmit and receive antennas, the appropriate configuration of pilot-data resources becomes a critical design aspect. In this article, we review recent advances in system design approaches that are designed for the acquisition of CSI and discuss some of the recent results that help to dimension the pilot and data resources specifically in cellular MU-MIMO systems
Transceiver design for single-cell and multi-cell downlink multiuser MIMO systems
This thesis designs linear transceivers for the down link multiple user
multiple input multiple output single-cell and multiple-cell systems. The
transceivers are designed by assuming perfect and imperfect channel state
information at the BS and mobile stations (MS). Different signal to
interference plus noise ratio, mean square error and rate-based design criteria
are considered. These design criteria are formulated by considering total BS,
per BS antenna, per user, per symbol or a combination of per BS antenna and per
user (symbol) power constraints. To solve these problems generalized down link
up link and down link interference duality approaches are proposed.
We have also shown that the weighted sum rate maximization problem can be
equivalently formulated as weighted sum mean square error minimization problem
with additional optimization variables and constraints. We also develop
distributed transceiver design algorithms to solve weighted sum rate and mean
square error optimization problems for coordinated BS systems. The distributed
transceiver design algorithms employ modify matrix fractional minimization and
Lagrangian dual decomposition methods.Comment: PhD Thesi
Multi-Cell Interference Exploitation: Enhancing the Power Efficiency in Cell Coordination
In this paper, we propose a series of novel coordination schemes for multi-cell downlink communication. Starting
from full base station (BS) coordination, we first propose a
fully-coordinated scheme to exploit beneficial effects of both
inter-cell and intra-cell interference, based on sharing both
channel state information (CSI) and data among the BSs. To
reduce the coordination overhead, we then propose a partiallycoordinated scheme where only intra-cell interference is designed
to be constructive while inter-cell is jointly suppressed by the
coordinated BSs. Accordingly, the coordination only involves
CSI exchange and the need for sharing data is eliminated.
To further reduce the coordination overhead, a third scheme
is proposed, which only requires the knowledge of statistical
inter-cell channels, at the cost of a slight increase on the
transmission power. For all the proposed schemes, imperfect
CSI is considered. We minimize the total transmission power in
terms of probabilistic and deterministic optimizations. Explicitly,
the former statistically satisfies the users’ signal-to-interferenceplus-noise ratio (SINR) while the latter guarantees the SINR
requirements in the worst case CSI uncertainties. Simulation
verifies that our schemes consume much lower power compared
to the existing benchmarks, i.e., coordinated multi-point (CoMP)
and coordinated-beamforming (CBF) systems, opening a new
dimension on multi-cell coordination
Multi-user spatial diversity techniques for wireless communication systems
Multiple antennas at the transmitter and receiver, formally known as multiple-input
multiple-output (MIMO) systems have the potential to either increase the data rates
through spatial multiplexing or enhance the quality of services through exploitation
of diversity. In this thesis, the problem of downlink spatial multiplexing, where a
base station (BS) serves multiple users simultaneously in the same frequency band is
addressed. Spatial multiplexing techniques have the potential to make huge saving
in the bandwidth utilization. We propose spatial diversity techniques with and without
the assumption of perfect channel state information (CSI) at the transmitter.
We start with proposing improvement to signal-to-leakage ratio (SLR) maximization
based spatial multiplexing techniques for both fiat fading and frequency selective
channels. [Continues.
Interference Exploitation in Full Duplex Communications: Trading Interference Power for Both Uplink and Downlink Power Savings
This paper considers a multiuser full-duplex (FD) wireless communication system, where a FD radio base station (BS) serves multiple single-antenna half-duplex (HD) uplink and downlink users simultaneously. Unlike conventional interference mitigation approaches, we propose to use the knowledge of the data symbols and the channel state information (CSI) at the FD radio BS to exploit the multi-user interference constructively rather than to suppress it. We propose a multi-objective optimization problem (MOOP) via the weighted Tchebycheff method to study the trade-off between the two desirable system design objectives namely the total downlink transmit power and the total uplink transmit power at the same time ensuring the required quality-of-service (QoS) for all users. In the proposed MOOP, we adapt the QoS constraints for the downlink users to accommodate constructive interference (CI) for both generic phase shift keying (PSK) modulated signals as well as for quadrature amplitude modulated (QAM) signals. We also extended our work to a robust design to study the system with imperfect uplink and downlink CSI. Simulation results and analysis show that significant power savings can be obtained. More importantly, however, the MOOP approach here allows for the power saved to be traded off for both uplink and downlink power savings, leading to an overall energy efficiency improvement in the wireless link
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