Fixed Power Constraint Research Articles

Refined Asymptotics for a Block Fading Channel Under Energy Harvesting and Fixed Power Constraints

We consider a block fading additive white Gaussian noise (AWGN) channel with perfect channel state information (CSI) at the transmitter (CSIT) and the receiver (CSIR). For a given codeword length and non-vanishing average probability of error, we obtain lower and upper bounds on the maximum transmission rate. First, we derive bounds when the transmitter has a time varying peak power constraint imposed by an energy harvesting device ; such devices power many modern wireless devices. Next, using the same techniques we obtain bounds for the canonical peak and average power constraint cases. The bounds characterize the finite blocklength back-off from the channel capacity, which is in turn achieved by water-filling power allocation across time. Finally, we derive bounds on the moderate deviations constant for the block fading model. We compare the bounds numerically to bring out the efficacy of our results.

Fine-grained Powercap Allocation for Power-constrained Systems based on Multi-objective Machine Learning

Power capping is an important solution to keep the system within a fixed power constraint. However, for the over-provisioned and power-constrained systems, especially the future exascale supercomputers, powercap needs to be reasonably allocated according to the workloads of compute nodes to achieve trade-offs among performance, energy and powercap. Thus it is necessary to model performance and energy and to predict the optimal powercap allocation strategies. Existing power allocation approaches have insufficient granularity within nodes. Modeling approaches usually model performance and energy separately, ignoring the correlation between objectives, and do not expose the Pareto-optimal powercap configurations. Therefore, this article combines the powercap with uncore frequency scaling and proposes an approach to predict the Pareto-optimal powercap configurations on the power-constrained system for input MPI and OpenMP parallel applications. Our approach first uses the elaborately designed micro-benchmarks and a small number of existing benchmarks to build the training set, and then applies a multi-objective machine learning algorithm which combines the stacked single-target method with extreme gradient boosting to build multi-objective models of performance and energy. The models can be used to predict the optimal processor and memory powercap settings, helping compute nodes perform fine-grained powercap allocation. When the optimal powercap configuration is determined, the uncore frequency scaling is used to further optimize the energy consumption. Compared with the reference powercap configuration, the predicted optimal configurations predicted by our method can achieve an average powercap reduction of 31.35 percent, an average energy reduction of 12.32 percent, and average performance degradation of only 2.43 percent.

Maximum Capacities in Submarine Cables With Fixed Power Constraints for C-Band, C+L-Band, and Multicore Fiber Systems

Achieving greater transmission capacity in submarine optical cables is of great interest as data traffic demands continue to increase worldwide. A significant constraint unique to submarine cable systems is that of electrical power that must be delivered to the entire cable from the terminals at the landing points. Recently, much focus has been on how to maximize the overall cable transmission capacity within fixed electrical power feed constraints. Until recently, all repeatered submarine cable systems were built using the erbium-doped fiber amplifier C-band, but C+L-band systems are now being considered and deployed. In parallel, there has been intense interest in spatial division multiplexing technologies, such as multicore fibers, as potential means to enabling greater transmission capacity in terrestrial and submarine systems. In this work, we examine maximum submarine cable capacities for three types of systems based on single-core fibers with C-band only or C+L-band transmission, and general multicore fiber systems with C-band-only transmission. The analysis is performed on the basis of common fixed power constraints and received signal-to-noise requirements, and comparable fiber-core characteristics. Additional losses for devices, such as C/L-band splitters and fan-in/fan-out modules, are accounted, and their impact on maximum cable capacity is estimated. For multicore fiber systems, other potential effects, such as higher fiber attenuation and crosstalk between cores, are also analyzed and evaluated with respect to capacity impacts. We find that single-core C-band systems offer the highest cable capacity, provided cable designs can accommodate the number of fiber pairs suggested.

Enhanced Power Allocation for Sum Rate Maximization in OFDM-NOMA VLC Systems

This letter investigates the power allocation problem for the downlink of an orthogonal frequency division multiple (OFDM)-based non-orthogonal multiple access visible light communication (NOMA-VLC) system. Unlike the commonly used two-user OFDM-NOMA VLC model, in this letter, an arbitrary number of multiplexed users is considered when formulating the sum rate maximization problem. Moreover, both user-level and subcarrier-level power optimization are taken into account to improve the system performance. The corresponding theoretical analysis is presented, with the consideration of optimal decoding order and each user's required signal-to-interference-plus-noise ratio (SINR). Given a fixed power constraint on each OFDM subcarrier, we derive the optimal power ratio for an arbitrary number of multiplexed users in OFDM-NOMA VLC. Numerical results show that with a required SINR of 3 dB, the proposed enhanced power allocation algorithm has 39.59% and 40.11% sum-rate enhancement when compared to optimized fixed power allocation algorithm and gain ratio power allocation algorithm, respectively.

Optimal communication scheduling and remote estimation over an additive noise channel

This paper considers a sequential sensor scheduling and remote estimation problem with one sensor and one estimator. The sensor makes sequential observations about the state of an underlying memoryless stochastic process, and makes a decision as to whether or not to send this measurement to the estimator. The sensor and the estimator have the common objective of minimizing expected distortion in the estimation of the state of the process, over a finite time horizon. The sensor is either charged a cost for each transmission or constrained on transmission times. As opposed to the prior work where communication between the sensor and the estimator was assumed to be perfect (noiseless), in this work an additive noise channel with fixed power constraint is considered; hence, the sensor has to encode its message before transmission. Under some technical assumptions, we obtain the optimal encoding and estimation policies within the piecewise affine class in conjunction with the optimal transmission schedule. The impact of the presence of a noisy channel is analyzed numerically based on dynamic programming. This analysis yields some rather surprising results such as a phase-transition phenomenon in the number of used transmission opportunities, which was not encountered in the noiseless communication setting.

Precoding design for STBC‐MIMO system with imperfect feedback in spatially correlated Rayleigh channel

By minimising the pairwise error probability (PEP) bound subject to the fixed power constraint, a suboptimal precoding scheme for space–time block-coded multiple-input–multiple-output (STBC-MIMO) systems with mean and covariance feedback in spatially correlated Rayleigh fading channels is developed, which can include the mean-feedback only and covariance-feedback only as its special cases. This scheme can achieve performances close to the existing optimal scheme while being more computationally efficient. The simulation results show that the proposed scheme can provide better performances than the conventional equal power scheme, and achieve almost the same performances as the existing optimal scheme.

Energy‐efficient resource allocation for amplify‐and‐forward relaying in OFDM systems

AbstractIn this paper, we study end‐to‐end energy efficiency of an orthogonal frequency‐division multiplexing relay‐based system under power constraints for the base station and relay node with system circuit power considerations. Using a two‐phase amplify‐and‐forward relaying protocol, we assume that relay has a fixed power constraint and the source power can vary in transmission power interval where the source employs a selective relaying mechanism for each individual subcarrier. Therefore, in our model, the source is able to adaptively select some subcarriers to be relayed. The radio resource allocation is then formulated as an energy‐efficient mixed binary integer programming, and then we propose a heuristic algorithm to find the suboptimal solution. The solution consists of the suboptimal transmit power of the source, the suboptimal set of subcarriers for relaying and the optimal transmit power of each subcarrier at the source and relay in the first and second time slots. The algorithm obtains energy‐efficient transmission power for a given relay transmission power based on a gradient descent method. Then a two‐step iterative scheme is proposed to obtain the subcarriers to be relayed as well as the optimal power allocation at the source and relay in the first and second time slots. To evaluate the efficiency of the proposed method, we compare its efficiency through simulations with the cases without using selective subcarrier relaying and without circuit power consideration in low and high relay transmit power regimes. The simulation results indicate that using our proposed method results in a significant improvement in the energy efficiency. Copyright © 2014 John Wiley & Sons, Ltd.

Cross-layer Design for MIMO Systems with Transmit Antenna Selection and Imperfect CSI

In this paper, by combining adaptive modulation and automatic repeat request (ARQ), a cross-layer design (CLD) scheme for multiple-input and multiple-output (MIMO) system with transmit antenna selection (TAS) and imperfect channel state information (CSI) is presented. Based on the imperfect CSI, the probability density function of the effective signal to noise ratio (SNR) is derived, and the fading gain switching thresholds are also derived subject to a target packet loss rate and fixed power constraint. According to these results, we further derive the average spectrum efficiency (SE) and packet error rate (PER) of the system. As a result, closed-form expressions of the average SE and PER are obtained, respectively. The derived expressions include the expressions under perfect CSI as special cases, and can provide good performance evaluation for the CLD system with imperfect CSI. Simulation results verify the validity of the theoretical analysis. The results show that the CLD system with TAS provides better SE than that with space-time block coding, but the SE and PER performance of the system with imperfect CSI are worse than those with perfect CSI due to the estimation error.

Optimal mixing and optimal stirring for fixed energy, fixed power, or fixed palenstrophy flows

We consider passive scalar mixing by a prescribed divergence-free velocity vector field in a periodic box and address the following question: Starting from a given initial inhomogeneous distribution of passive tracers, and given a certain energy budget, power budget, or finite palenstrophy budget, what incompressible flow field best mixes the scalar quantity? We focus on the optimal stirring strategy recently proposed by Lin et al. [“Optimal stirring strategies for passive scalar mixing,” J. Fluid Mech. 675, 465 (2011)]10.1017/S0022112011000292 that determines the flow field that instantaneously maximizes the depletion of the H−1 mix-norm. In this work, we bridge some of the gap between the best available a priori analysis and simulation results. After recalling some previous analysis, we present an explicit example demonstrating finite-time perfect mixing with a finite energy constraint on the stirring flow. On the other hand, using a recent result by Wirosoetisno et al. [“Long time stability of a classical efficient scheme for two dimensional Navier-Stokes equations,” SIAM J. Numer. Anal. 50(1), 126–150 (2012)]10.1137/110834901 we establish that the H−1 mix-norm decays at most exponentially in time if the two-dimensional incompressible flow is constrained to have constant palenstrophy. Finite-time perfect mixing is thus ruled out when too much cost is incurred by small scale structures in the stirring. Direct numerical simulations in two dimensions suggest the impossibility of finite-time perfect mixing for flows with fixed power constraint and we conjecture an exponential lower bound on the H−1 mix-norm in this case. We also discuss some related problems from other areas of analysis that are similarly suggestive of an exponential lower bound for the H−1 mix-norm.

Cross-Layer Design for Space-Time coded MIMO Systems over Rice Fading Channel

Abstract A cross-layer design (CLD) scheme for space-time coded MIMO systems over Rice fading channel is presented by combining adaptive modulation and automatic repeat request, and the corresponding system performance is investigated well. The fading gain switching thresholds subject to a target packet error rate (PER) and fixed power constraint are derived. According to these results, and using the generalized Marcum Q-function, the calculation formulae of the average spectrum efficiency (SE) and PER of the system with CLD are derived. As a result, closed-form expressions for average SE and PER are obtained. These expressions include some existing expressions in Rayleigh channel as special cases. With these expressions, the system performance in Rice fading channel is evaluated effectively. Numerical results verify the validity of the theoretical analysis. The results show that the system performance in Rice channel is effectively improved as Rice factor increases, and outperforms that in Rayleigh channel.

Performance of Cross-Layer Design with Antenna Selection and Imperfect Feedback Information in MIMO Systems

By combining adaptive modulation and automatic repeat request, a cross-layer design (CLD) scheme for MIMO system with antenna selection (AS) and imperfect feedback is presented, and the corresponding performance is studied. Subject to a target packet loss rate and fixed power constraint, the variable switching thresholds of fading gain are derived. According to these results, and using mathematical manipulation, the average spectrum efficiency (SE) and packet error rate (PER) of the system are further derived. As a result, closed-form expressions of the average SE and PER are obtained, respectively. These expressions include the expressions under perfect channel state information as special cases and provide good performance evaluation for the system. Numerical results show that the proposed CLD scheme with antenna selection has higher SE than the existing CLD scheme with space-time block coding, and the CLD scheme with variable switching thresholds outperforms that with conventional-fixed switching thresholds.

Performance of Adaptive Modulation with STBC and Imperfect Feedback Information over Rayleigh Fading Channel

Based on imperfect channel information feedback, t he performance of space-time coded multi-antenna systems with adaptive modulation and feedback delay is investigated in Rayleigh fading channel , and the corresponding theoretical analysis for spectrum efficiency (SE) and bit error rate (BER) is presented . T he fading gain value is partitioned into a number of regions by which the modulation is adapted in terms of the region the fading gain falls in . The fading gain switching thresholds for attaining maximum spectrum efficiency under a target BER and fixed power constraint are achieved. Based on the se results, we derive the theoretical calculation formulae for the system spectrum efficiency and average BER in detail. As a result, the closed-form expressions for the spectrum efficiency and average BER are respectively obtained for perfect feedback . Besides, the system performance with delayed feedback information is analyzed, and t he accurate and approximate BER expressions of the systems with imperfect feedback are derived, respectively. The obtained theoretical formulae will have more accuracy than the existing formulae. Simulation results show that the theoretical SE and BER are in good agreement with the corresponding simulated values, and the system has slight BER performance degradation for the normalized time delay less than 0.01.

Power capping: a prelude to power shifting

We present a technique that controls the peak power consumption of a high-density server by implementing a feedback controller that uses precise, system-level power measurement to periodically select the highest performance state while keeping the system within a fixed power constraint. A control theoretic methodology is applied to systematically design this control loop with analytic assurances of system stability and controller performance, despite unpredictable workloads and running environments. In a real server we are able to control power over a 1 second period to within 1 W and over an 8 second period to within 0.1 W. Conventional servers respond to power supply constraint situations by using simple open-loop policies to set a safe performance level in order to limit peak power consumption. We show that closed-loop control can provide higher performance under these conditions and implement this technique on an IBM BladeCenter HS20 server. Experimental results demonstrate that closed-loop control provides up to 82% higher application performance compared to open-loop control and up to 17% higher performance compared to a widely used ad-hoc technique.