65,092 research outputs found
Energy-efficient multiuser SIMO: Achieving probabilistic robustness with Gaussian channel uncertainty
This paper addresses the joint optimization of power control and receive beamforming vectors for a multiuser singleinput multiple-output (SIMO) antenna system in the uplink in which mobile users are single-antenna transmitters and the base station receiver has multiple antennas. Channel state information at the receiver (CSIR) is exploited but the CSIR is imperfect with its uncertainty being modeled as a random Gaussian matrix. Our objective is to devise an energy-efficient solution to minimize the individual users' transmit power while meeting the users' signal-to-interference plus noise ratio (SINR) constraints, under the consideration of CSIR and its error characteristics. This is achieved by solving a sum-power minimization problem, subject to a collection of users' outage probability constraints on their target SINRs. Regarding the signal power minus the sum of inter-user interferences (SMI) power as Gaussian, an iterative and convergent algorithm which is proved to reach the global optimum for the joint power allocation and receive beamforming solution, is proposed, though the optimization problem is indeed non-convex. A systematic scheme to detect feasibility and find a feasible initial solution, if there exists any, is also devised. Simulation results verify the use of Gaussian approximation and robustness of the proposed algorithm in terms of users' probability constraints, and indicate a significant performance gain as compared to the zero-forcing (ZF) and minimum meansquare-error (MMSE) beamforming systems. © 2009 IEEE.published_or_final_versio
Energy-Efficient Resource Allocation in Time Division Multiple-Access over Fading Channels
We investigate energy-efficiency issues and resource allocation policies for
time division multi-access (TDMA) over fading channels in the power-limited
regime. Supposing that the channels are frequency-flat block-fading and
transmitters have full or quantized channel state information (CSI), we first
minimize power under a weighted sum-rate constraint and show that the optimal
rate and time allocation policies can be obtained by water-filling over
realizations of convex envelopes of the minima for cost-reward functions. We
then address a related minimization under individual rate constraints and
derive the optimal allocation policies via greedy water-filling. Using
water-filling across frequencies and fading states, we also extend our results
to frequency-selective channels. Our approaches not only provide fundamental
power limits when each user can support an infinite number of
capacity-achieving codebooks, but also yield guidelines for practical designs
where users can only support a finite number of adaptive modulation and coding
(AMC) modes with prescribed symbol error probabilities, and also for systems
where only discrete-time allocations are allowed.Comment: 45 pages, 9 figures, submitted to IEEE Transactions on Information
Theor
NOMA-based Energy-Efficient Wireless Powered Communications
In this paper, we study the performance of non-orthogonal multiple access
(NOMA) schemes in wireless powered communication networks (WPCN) focusing on
the system energy efficiency (EE). We consider multiple energy harvesting user
equipments (UEs) that operate based on harvest-then-transmit protocol. The
uplink information transfer is carried out by using power-domain multiplexing,
and the receiver decodes each UE's data in such a way that the UE with the best
channel gain is decoded without interference. In order to determine optimal
resource allocation strategies, we formulate optimization problems considering
two models, namely half-duplex and asynchronous transmission, based on how
downlink and uplink operations are coordinated. In both cases, we have
concave-linear fractional problems, and hence Dinkelbach's method can be
applied to obtain the globally optimal solutions. Thus, we first derive
analytical expressions for the harvesting interval, and then we provide an
algorithm to describe the complete procedure. Furthermore, we incorporate
delay-limited sources and investigate the impact of statistical queuing
constraints on the energy-efficient allocation of operating intervals. We
formulate an optimization problem that maximizes the system effective-EE while
UEs are applying NOMA scheme for uplink information transfer. Since the problem
satisfies pseudo-concavity, we provide an iterative algorithm using bisection
method to determine the unique solution. In the numerical results, we observe
that broadcasting at higher power level is more energy efficient for WPCN with
uplink NOMA. Additionally, exponential decay QoS parameter has considerable
impact on the optimal solution, and in the presence of strict constraints, more
time is allocated for downlink interval under half-duplex operation with uplink
TDMA mode.Comment: 31 pages, 12 figures, to appear on IEEE Transactions on Green
Communications and Networkin
Energy Efficient Power and Channel Allocation in Underlay Device to Multi Device Communications
In this paper, we optimize the energy efficiency (bits/s/Hz/J) of
device-to-multi-device (D2MD) wireless communications. While the
device-to-device scenario has been extensively studied to improve the spectral
efficiency in cellular networks, the use of multicast communications opens the
possibility of reusing the spectrum resources also inside the groups. The
optimization problem is formulated as a mixed integer non-linear joint
optimization for the power control and allocation of resource blocks (RBs) to
each group. Our model explicitly considers resource sharing by letting
co-channel transmission over a RB (up to a maximum of r transmitters) and/or
transmission through s different channels in each group. We use an iterative
decomposition approach, using first matching theory to find a stable even if
sub-optimal channel allocation, to then optimize the transmission power vectors
in each group via fractional programming. Additionally, within this framework,
both the network energy efficiency and the max-min individual energy efficiency
are investigated. We characterize numerically the energy-efficient capacity
region, and our results show that the normalized energy efficiency is nearly
optimal (above 90 percent of the network capacity) for a wide range of
minimum-rate constraints. This performance is better than that of other
matching-based techniques previously proposed
Weighted Sum-Throughput Maximization for Energy Harvesting Powered MIMO Multi-Access Channels
This paper develops a novel approach to obtaining the optimal scheduling
strategy in a multi-input multi-output (MIMO) multi-access channel (MAC), where
each transmitter is powered by an individual energy harvesting process. Relying
on the state-of-the-art convex optimization tools, the proposed approach
provides a low-complexity block coordinate ascent algorithm to obtain the
optimal transmission policy that maximizes the weighted sum-throughput for MIMO
MAC. The proposed approach can provide the optimal benchmarks for all practical
schemes in energy-harvesting powered MIMO MAC transmissions. Based on the
revealed structure of the optimal policy, we also propose an efficient online
scheme, which requires only causal knowledge of energy arrival realizations.
Numerical results are provided to demonstrate the merits of the proposed novel
scheme.Comment: 9 pages, 8 figures, 1 tabl
Power allocation in wireless multi-user relay networks
In this paper, we consider an amplify-and-forward wireless relay system where multiple source nodes communicate with their corresponding destination nodes with the help of relay nodes. Conventionally, each relay equally distributes the available resources to its relayed sources. This approach is clearly sub-optimal since each user experiences dissimilar channel conditions, and thus, demands different amount of allocated resources to meet its quality-of-service (QoS) request. Therefore, this paper presents novel power allocation schemes to i) maximize the minimum signal-to-noise ratio among all users; ii) minimize the maximum transmit power over all sources; iii) maximize the network throughput. Moreover, due to limited power, it may be impossible to satisfy the QoS requirement for every user. Consequently, an admission control algorithm should first be carried out to maximize the number of users possibly served. Then, optimal power allocation is performed. Although the joint optimal admission control and power allocation problem is combinatorially hard, we develop an effective heuristic algorithm with significantly reduced complexity. Even though theoretically sub-optimal, it performs remarkably well. The proposed power allocation problems are formulated using geometric programming (GP), a well-studied class of nonlinear and nonconvex optimization. Since a GP problem is readily transformed into an equivalent convex optimization problem, optimal solution can be obtained efficiently. Numerical results demonstrate the effectiveness of our proposed approach
Energy-Efficient Joint User-RB Association and Power Allocation for Uplink Hybrid NOMA-OMA
In this paper, energy efficient resource allocation is considered for an
uplink hybrid system, where non-orthogonal multiple access (NOMA) is integrated
into orthogonal multiple access (OMA). To ensure the quality of service for the
users, a minimum rate requirement is pre-defined for each user. We formulate an
energy efficiency (EE) maximization problem by jointly optimizing the user
clustering, channel assignment and power allocation. To address this hard
problem, a many-to-one bipartite graph is first constructed considering the
users and resource blocks (RBs) as the two sets of nodes. Based on swap
matching, a joint user-RB association and power allocation scheme is proposed,
which converges within a limited number of iterations. Moreover, for the power
allocation under a given user-RB association, we first derive the feasibility
condition. If feasible, a low-complexity algorithm is proposed, which obtains
optimal EE under any successive interference cancellation (SIC) order and an
arbitrary number of users. In addition, for the special case of two users per
cluster, analytical solutions are provided for the two SIC orders,
respectively. These solutions shed light on how the power is allocated for each
user to maximize the EE. Numerical results are presented, which show that the
proposed joint user-RB association and power allocation algorithm outperforms
other hybrid multiple access based and OMA-based schemes.Comment: Non-orthogonal multiple access (NOMA), energy efficiency (EE), power
allocation (PA), uplink transmissio
A Survey on MIMO Transmission with Discrete Input Signals: Technical Challenges, Advances, and Future Trends
Multiple antennas have been exploited for spatial multiplexing and diversity
transmission in a wide range of communication applications. However, most of
the advances in the design of high speed wireless multiple-input multiple
output (MIMO) systems are based on information-theoretic principles that
demonstrate how to efficiently transmit signals conforming to Gaussian
distribution. Although the Gaussian signal is capacity-achieving, signals
conforming to discrete constellations are transmitted in practical
communication systems. As a result, this paper is motivated to provide a
comprehensive overview on MIMO transmission design with discrete input signals.
We first summarize the existing fundamental results for MIMO systems with
discrete input signals. Then, focusing on the basic point-to-point MIMO
systems, we examine transmission schemes based on three most important criteria
for communication systems: the mutual information driven designs, the mean
square error driven designs, and the diversity driven designs. Particularly, a
unified framework which designs low complexity transmission schemes applicable
to massive MIMO systems in upcoming 5G wireless networks is provided in the
first time. Moreover, adaptive transmission designs which switch among these
criteria based on the channel conditions to formulate the best transmission
strategy are discussed. Then, we provide a survey of the transmission designs
with discrete input signals for multiuser MIMO scenarios, including MIMO uplink
transmission, MIMO downlink transmission, MIMO interference channel, and MIMO
wiretap channel. Additionally, we discuss the transmission designs with
discrete input signals for other systems using MIMO technology. Finally,
technical challenges which remain unresolved at the time of writing are
summarized and the future trends of transmission designs with discrete input
signals are addressed.Comment: 110 pages, 512 references, submit to Proceedings of the IEE
Energy Efficiency in Multiuser Transmission Over Parallel Frequency Channels
Energy efficiency is an important design criterion for wireless
communications. When parallel frequency channels are used for multiuser
transmission, the channel bandwidths and user power are adjusted to maximize
the sum information rate with the bandwidth budget, the transmit power budget,
and the user-specific rate requirements. The maximum sum rate is used in
measuring the energy efficiency. With fixed or flexible bandwidths of the
frequency channels, practical methods are developed to find the total transmit
power with the unique optimal resource (bandwidth and power) allocation for
maximum energy efficiency. This resource allocation ensures that, while each
user's minimum rate requirement is satisfied, all the excess resource of the
spectrum and transmit power is dedicated to the one user with the best channel
quality. Simulation results validate the optimal solutions of total transmit
power and resource allocation that support the energy-efficient multiuser
transmission.Comment: 10 pages, 9 figure
Optimal and Robust Power Allocation for Visible Light Positioning Systems under Illumination Constraints
The problem of optimal power allocation among light emitting diode (LED)
transmitters in a visible light positioning (VLP) system is considered for the
purpose of improving localization performance of visible light communication
(VLC) receivers. Specifically, the aim is to minimize the Cram\'{e}r-Rao lower
bound (CRLB) on the localization error of a VLC receiver by optimizing LED
transmission powers in the presence of practical constraints such as individual
and total power limitations and illuminance constraints. The formulated
optimization problem is shown to be convex and thus can efficiently be solved
via standard tools. We also investigate the case of imperfect knowledge of
localization parameters and develop robust power allocation algorithms by
taking into account both overall system uncertainty and individual parameter
uncertainties related to the location and orientation of the VLC receiver. In
addition, we address the total power minimization problem under predefined
accuracy requirements to obtain the most energy-efficient power allocation
vector for a given CRLB level. Numerical results illustrate the improvements in
localization performance achieved by employing the proposed optimal and robust
power allocation strategies over the conventional uniform and non-robust
approaches.Comment: 31 pages, 7 figure
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