Impact of power allocation strategies in long-haul few-mode fiber transmission systems

We report for the first time on the limitations in the operational power range of few-mode fiber based transmission systems, employing 28Gbaud quadrature phase shift keying transponders, over 1,600km. It is demonstrated that if an additional mode is used on a preexisting few-mode transmission link, and allowed to optimize its performance, it will have a significant impact on the pre-existing mode. In particular, we show that for low mode coupling strengths (weak coupling regime), the newly added variable power mode does not considerably impact the fixed power existing mode, with performance penalties less than 2dB (in Q-factor). On the other hand, as mode coupling strength is increased (strong coupling regime), the individual launch power optimization significantly degrades the system performance, with penalties up to ∼6dB. Our results further suggest that mutual power optimization, of both fixed power and variable power modes, reduces power allocation related penalties to less than 3dB, for any given coupling strength, for both high and low differential mode delays. © 2013 Optical Society of America.

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.

Optimal Power Allocation for Multiuser Secure Communication in Cooperative Relaying Networks

We consider a cooperative relaying network in which a source communicates with a group of users in the presence of one eavesdropper. We assume that there are no source-user links and the group of users receive only retransmitted signal from the relay. Whereas, the eavesdropper receives both the original and retransmitted signals. Under these assumptions, we exploit the user selection technique to enhance the secure performance. We first find the optimal power allocation strategy when the source has the full channel state information (CSI) of all links. We then evaluate the security level through: i) ergodic secrecy rate and ii) secrecy outage probability when having only the statistical knowledge of CSIs.

I/Q imbalance in two-way AF relaying: Power allocation and performance analysis

We investigate the performance of dual-hop two-way amplify-and-forward (AF) relaying in the presence of inphase and quadrature-phase imbalance (IQI) at the relay node. In particular, the effective signal-to-interference-plus-noise ratio (SINR) at both sources is derived. These SINRs are used to design an instantaneous power allocation scheme, which maximizes the minimum SINR of the two sources under a total transmit power constraint. The solution to this optimization problem is analytically determined and used to evaluate the outage probability (OP) of the considered two-way AF relaying system. Both analytical and numerical results show that IQI can create fundamental performance limits on two-way relaying, which cannot be avoided by simply improving the channel conditions.

Optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers

For multiple heterogeneous multicore server processors across clouds and data centers, the aggregated performance of the cloud of clouds can be optimized by load distribution and balancing. Energy efficiency is one of the most important issues for large-scale server systems in current and future data centers. The multicore processor technology provides new levels of performance and energy efficiency. The present paper aims to develop power and performance constrained load distribution methods for cloud computing in current and future large-scale data centers. In particular, we address the problem of optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers. Our strategy is to formulate optimal power allocation and load distribution for multiple servers in a cloud of clouds as optimization problems, i.e., power constrained performance optimization and performance constrained power optimization. Our research problems in large-scale data centers are well-defined multivariable optimization problems, which explore the power-performance tradeoff by fixing one factor and minimizing the other, from the perspective of optimal load distribution. It is clear that such power and performance optimization is important for a cloud computing provider to efficiently utilize all the available resources. We model a multicore server processor as a queuing system with multiple servers. Our optimization problems are solved for two different models of core speed, where one model assumes that a core runs at zero speed when it is idle, and the other model assumes that a core runs at a constant speed. Our results in this paper provide new theoretical insights into power management and performance optimization in data centers.

Fast and efficient user pairing and power allocation algorithm for non-orthogonal multiple access in cellular networks

Non-orthogonal multiple access (NOMA) is emerging as a promising multiple access technology for the fifth generation cellular networks to address the fast growing mobile data traffic. It applies superposition coding in transmitters, allowing simultaneous allocation of the same frequency resource to multiple intra-cell users. Successive interference cancellation is used at the receivers to cancel intra-cell interference. User pairing and power allocation (UPPA) is a key design aspect of NOMA. Existing UPPA algorithms are mainly based on exhaustive search method with extensive computation complexity, which can severely affect the NOMA performance. A fast proportional fairness (PF) scheduling based UPPA algorithm is proposed to address the problem. The novel idea is to form user pairs around the users with the highest PF metrics with pre-configured fixed power allocation. Systemlevel simulation results show that the proposed algorithm is significantly faster (seven times faster for the scenario with 20 users) with a negligible throughput loss than the existing exhaustive search algorithm.

Interference-aware coordinated power allocation in autonomous Wi-Fi environment

Self-managed access points (APs) with growing intelligence can optimize their own performances but pose potential negative impacts on others without energy ef ciency. In this paper, we focus on modeling the coordinated interaction among interest-independent and self-con gured APs, and conduct the power allocation case study in the autonomous Wi-Fi scenario. Speci cally, we build a `coordination Wi-Fi platform (CWP), a public platform for APs interacting with each other. OpenWrt-based APs in the physical world are mapped to virtual agents (VAs) in CWP, which communicate with each other through a standard request-reply process de ned as AP talk protocol (ATP).With ATP, an active interference measurement methodology is proposed re ecting both in-range interference and hidden terminal interference, and the Nash bargaining-based power control is further formulated for interference reductions. CWP is deployed in a real of ce environment, where coordination interactions between VAs can bring a maximum 40-Mb/s throughput improvement with the Nash bargaining-based power control in the multi-AP experiments.

Subcarrier pairing and relay assignment with improved user fairness in a multi-user cooperative OFDM system

We consider a joint relay selection and subcarrier allocation problem that minimizes the total system power for a multi-user, multi-relay and single source cooperative OFDM based two hop system. The system is constrained to all users having a specific subcarrier requirement (user fairness). However no specific fairness constraints for relays are considered. To ensure the optimum power allocation, the subcarriers in two hops are paired with each other. We obtain an optimal subcarrier allocation for the single user case using a similar method to what is described in [1] and modify the algorithm for multiuser scenario. Although the optimality is not achieved in multiuser case the probability of all users being served fairly is improved significantly with a relatively low cost trade off.

Constellation Constrained Capacity of Two-user Broadcast Channels

Capacity region for two-user Gaussian Broadcast Channels (GBC) is well known with the optimal input being Gaussian. In this paper we explore the capacity region for GBC when the users' symbols are taken from finite complex alphabets (like M-QAM, M-PSK). When the alphabets for both the users are the same we show that rotation of one of the alphabets enlarges the capacity region. We arrive at an optimal angle of rotation by simulation. The effect of rotation on the capacity region at different SNRs is also studied using simulation results. Using the setup of Fading Broadcast Channel (FBC) given by [Li and Goldsmith, 2001], we study the ergodic capacity region with inputs from finite complex alphabets. It is seen that, using the procedure for optimum power allocation obtained in [Li and Goldsmith, 2001] for Gaussian inputs, to allocate power to symbols from finite complex alphabets, relative rotation between the alphabets does not improve the capacity region. Simulation results for a modified heuristic power allocation procedure for finite-constellation case, show that Constellation Constrained capacity region enlarges with rotation.

Density evolution and power profile optimization for iterative multiuser decoders based on individually optimum multiuser detectors

Iterative multiuser joint decoding based on exact Belief Propagation (BP) is analyzed in the large system limit by means of the replica method. It is shown that performance can be improved by appropriate power assignment to the users. The optimum power assignment can be found by linear programming in most technically relevant cases. The performance of BP iterative multiuser joint decoding is compared to suboptimum approximations based on Interference Cancellation (IC). While IC receivers show a significant loss for equal-power users, they yield performance close to BP under optimum power assignment.

Optimum wireless power transmission for sensors embedded in concrete

Various nondestructive testing (NDT) technologies for construction and performance monitoring have been studied for decades. Recently, the rapid evolution of wireless sensor network (WSN) technologies has enabled the development of sensors that can be embedded in concrete to monitor the structural health of infrastructure. Such sensors can be buried inside concrete and they can collect and report valuable volumetric data related to the health of a structure during and/or after construction. Wireless embedded sensors monitoring system is also a promising solution for decreasing the high installation and maintenance cost of the conventional wire based monitoring systems. Wireless monitoring sensors need to operate for long time. However, sensor batteries have finite life-time. Therefore, in order to enable long operational life of wireless sensors, novel wireless powering methods, which can charge the sensors’ rechargeable batteries wirelessly, need to be developed. The optimization of RF wireless powering of sensors embedded in concrete is studied here. First, our analytical results focus on calculating the transmission loss and propagation loss of electromagnetic waves penetrating into plain concrete at different humidity conditions for various frequencies. This analysis specifically leads to the identification of an optimum frequency range within 20–80 MHz that is validated through full-wave electromagnetic simulations. Second, the effects of various reinforced bar configurations on the efficiency of wireless powering are investigated. Specifically, effects of the following factors are studied: rebar types, rebar period, rebar radius, depth inside concrete, and offset placement. This analysis leads to the identification of the 902–928 MHz ISM band as the optimum power transmission frequency range for sensors embedded in reinforced concrete, since antennas working in this band are less sensitive to the effects of varying humidity as well as rebar configurations. Finally, optimized rectennas are designed for receiving and/or harvesting power in order to charge the rechargeable batteries of the embedded sensors. Such optimized wireless powering systems exhibit significantly larger efficiencies than the efficiencies of conventional RF wireless powering systems for sensors embedded in plain or reinforced concrete.

Optimal allocation of a cross-connection and sectionalizers in distribution systems

In this paper, the placement of sectionalizers, as well as, a cross-connection is optimally determined so that the objective function is minimized. The objective function employed in this paper consists of two main parts, the switch cost and the reliability cost. The switch cost is composed of the cost of sectionalizers and cross-connection and the reliability cost is assumed to be proportional to a reliability index, SAIDI. To optimize the allocation of sectionalizers and cross-connection problem realistically, the cost related to each element is considered as discrete. In consequence of binary variables for the availability of sectionalizers, the problem is extremely discrete. Therefore, the probability of local minimum risk is high and a heuristic-based optimization method is needed. A Discrete Particle Swarm Optimization (DPSO) is employed in this paper to deal with this discrete problem. Finally, a testing distribution system is used to validate the proposed method.

Dispersion of corona ions downwind from a high-voltage power line

Corona discharge is responsible for the small ions found near overhead power lines, and these are capable of modifying the ambient electrical environment such as the dc electric field at ground level (Fews, Wilding et al. 2002). Once produced, small ions quickly attach to aerosol particles in the air, producing ‘large ions’ which are roughly 1 nm to 1 µm in diameter. However, very few studies have reported measurements of ions produced by power lines and its impact on particle charge concentrations. In this present study, the measurements were conducted as a function of normal downwind distance from a 275kV power line for investigating the effect of corona ions on air ions, aerosol particle charge concentration and dc e-filed.

Low complexity Bit allocation algorithms for AAC encoding

We have developed two reduced complexity bit-allocation algorithms for MP3/AAC based audio encoding, which can be useful at low bit-rates. One algorithm derives optimum bit-allocation using constrained optimization of weighted noise-to-mask ratio and the second algorithm uses decoupled iterations for distortion control and rate control, with convergence criteria. MUSHRA based evaluation indicated that the new algorithm would be comparable to AAC but requiring only about 1/10 th the complexity.

Diversity-Rate Trade-off for Fading Channels with Power Control

We consider a complex, additive, white Gaussian noise channel with flat fading. We study its diversity order vs transmission rate for some known power allocation schemes. The capacity region is divided into three regions. For one power allocation scheme, the diversity order is exponential throughout the capacity region. For selective channel inversion (SCI) scheme, the diversity order is exponential in low and high rate region but polynomial in mid rate region. For fast fading case we also provide a new upper bound on block error probability and a power allocation scheme that minimizes it. The diversity order behaviour of this scheme is same as for SCI but provides lower BER than the other policies.