Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

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.

Network reconfiguration and loss allocation for distribution systems with distributed generation

Distribution systems with distributed generation require new analysis methods since networks are not longer passive. Two of the main problems in this new scenario are the network reconfiguration and the loss allocation. This work presents a distribution systems graphic simulator, developed with reconfiguration functions and a special focus on loss allocation, both considering the presence of distributed generation. This simulator uses a fast and robust power flow algorithm based on the current summation backward-forward technique. Reconfiguration problem is solved through a heuristic methodology and the losses allocation function, based on the Zbus method, is presented as an attached result for each obtained configuration. Results are presented and discussed, remarking the easiness of analysis through the graphic simulator as an excellent tool for planning and operation engineers, and very useful for training. © 2004 IEEE.

Network reconfiguration and loss allocation in a deregulated environment of distribution systems

Low flexibility and reliability in the operation of radial distribution networks make those systems be constructed with extra equipment as sectionalising switches in order to reconfigure the network, so the operation quality of the network can be improved. Thus, sectionalising switches are used for fault isolation and for configuration management (reconfiguration). Moreover, distribution systems are being impacted by the increasing insertion of distributed generators. Hence, distributed generation became one of the relevant parameters in the evaluation of systems reconfiguration. Distributed generation may affect distribution networks operation in various ways, causing noticeable impacts depending on its location. Thus, the loss allocation problem becomes more important considering the possibility of open access to the distribution networks. In this work, a graphic simulator for distribution networks with reconfiguration and loss allocation functions, is presented. Reconfiguration problem is solved through a heuristic methodology, using a robust power flow algorithm based on the current summation backward-forward technique, considering distributed generation. Four different loss allocation methods (Zbus, Direct Loss Coefficient, Substitution and Marginal Loss Coefficient) are implemented and compared. Results for a 32-bus medium voltage distribution network, are presented and discussed.

Iterative bit- and power allocation in correlated MIMO systems

In this contribution a novel iterative bit- and power allocation (IBPA) approach has been developed when transmitting a given bit/s/Hz data rate over a correlated frequency non-selective (4× 4) Multiple-Input MultipleOutput (MIMO) channel. The iterative resources allocation algorithm developed in this investigation is aimed at the achievement of the minimum bit-error rate (BER) in a correlated MIMO communication system. In order to achieve this goal, the available bits are iteratively allocated in the MIMO active layers which present the minimum transmit power requirement per time slot.

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.

Distributed power control algorithm for multiple access systems based on Verhulst model

In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.

An Explicit GTS allocation algorithm for IEEE 802.15.4

The IEEE 802.15.4 standard provides appealing features to simultaneously support real-time and non realtime traffic, but it is only capable of supporting real-time communications from at most seven devices. Additionally, it cannot guarantee delay bounds lower than the superframe duration. Motivated by this problem, in this paper we propose an Explicit Guaranteed time slot Sharing and Allocation scheme (EGSA) for beacon-enabled IEEE 802.15.4 networks. This scheme is capable of providing tighter delay bounds for real-time communications by splitting the Contention Free access Period (CFP) into smaller mini time slots and by means of a new guaranteed bandwidth allocation scheme for a set of devices with periodic messages. At the same the novel bandwidth allocation scheme can maximize the duration of the CFP for non real-time communications. Performance analysis results show that the EGSA scheme works efficiently and outperforms competitor schemes both in terms of guaranteed delay and bandwidth utilization.

Optimum power allocation for parallel Gaussian channels with arbitrary input distributions

The mutual information of independent parallel Gaussian-noise channels is maximized, under an average power constraint, by independent Gaussian inputs whose power is allocated according to the waterfilling policy. In practice, discrete signalling constellations with limited peak-to-average ratios (m-PSK, m-QAM, etc) are used in lieu of the ideal Gaussian signals. This paper gives the power allocation policy that maximizes the mutual information over parallel channels with arbitrary input distributions. Such policy admits a graphical interpretation, referred to as mercury/waterfilling, which generalizes the waterfilling solution and allows retaining some of its intuition. The relationship between mutual information of Gaussian channels and nonlinear minimum mean-square error proves key to solving the power allocation problem.

Optimum power allocation for multiuser OFDM with arbitrary signal constellations

This paper formulates power allocation policies that maximize the region of mutual informationsachievable in multiuser downlink OFDM channels. Arbitrary partitioning ofthe available tones among users and arbitrary modulation formats, possibly different forevery user, are considered. Two distinct policies are derived, respectively for slow fadingchannels tracked instantaneously by the transmitter and for fast fading channels knownonly statistically thereby. With instantaneous channel tracking, the solution adopts theform of a multiuser mercury/waterfilling procedure that generalizes the single-user mercury/waterfilling introduced in [1, 2]. With only statistical channel information, in contrast,the mercury/waterfilling interpretation is lost. For both policies, a number of limitingregimes are explored and illustrative examples are provided.

A robust nonlinear identification algorithm using PRESS statistic and forward regression

This letter introduces a new robust nonlinear identification algorithm using the Predicted REsidual Sums of Squares (PRESS) statistic and for-ward regression. The major contribution is to compute the PRESS statistic within a framework of a forward orthogonalization process and hence construct a model with a good generalization property. Based on the properties of the PRESS statistic the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation.

Robust blind deconvolution algorithm: variance approximation and series decoupling

An alternative blind deconvolution algorithm for white-noise driven minimum phase systems is presented and verified by computer simulation. This algorithm uses a cost function based on a novel idea: variance approximation and series decoupling (VASD), and suggests that not all autocorrelation function values are necessary to implement blind deconvolution.