Javier Rodríguez Fonollosa

Practical algorithms for a family of waterfilling solutions

Many engineering problems that can be formulated as constrained optimization problems result in solutions given by a waterfilling structure; the classical example is the capacity-achieving solution for a frequency-selective channel. For simple waterfilling solutions with a single waterlevel and a single constraint (typically, a power constraint), some algorithms have been proposed in the literature to compute the solutions numerically. However, some other optimization problems result in significantly more complicated waterfilling solutions that include multiple waterlevels and multiple constraints. For such cases, it may still be possible to obtain practical algorithms to evaluate the solutions numerically but only after a painstaking inspection of the specific waterfilling structure. In addition, a unified view of the different types of waterfilling solutions and the corresponding practical algorithms is missing. The purpose of this paper is twofold. On the one hand, it overviews the waterfilling results existing in the literature from a unified viewpoint. On the other hand, it bridges the gap between a wide family of waterfilling solutions and their efficient implementation in practice; to be more precise, it provides a practical algorithm to evaluate numerically a general waterfilling solution, which includes the currently existing waterfilling solutions and others that may possibly appear in future problems.

Capacity of MIMO channels: asymptotic evaluation under correlated fading

This paper investigates the asymptotic uniform power allocation capacity of frequency nonselective multiple-input multiple-output channels with fading correlation at either the transmitter or the receiver. We consider the asymptotic situation, where the number of inputs and outputs increase without bound at the same rate. A simple uniparametric model for the fading correlation function is proposed and the asymptotic capacity per antenna is derived in closed form. Although the proposed correlation model is introduced only for mathematical convenience, it is shown that its shape is very close to an exponentially decaying correlation function. The asymptotic expression obtained provides a simple and yet useful way of relating the actual fading correlation to the asymptotic capacity per antenna from a purely analytical point of view. For example, the asymptotic expressions indicate that fading correlation is more harmful when arising at the side with less antennas. Moreover, fading correlation does not influence the rate of growth of the asymptotic capacity per receive antenna with high E/sub b//N/sub 0/.

Blind channel estimation and data detection using hidden Markov models

We propose applying the hidden Markov models (HMM) theory to the problem of blind channel estimation and data detection. The Baum-Welch (BW) algorithm, which is able to estimate all the parameters of the model, is enriched by introducing some linear constraints emerging from a linear FIR hypothesis on the channel. Additionally, a version of the algorithm that is suitable for time-varying channels is also presented. Performance is analyzed in a GSM environment using standard test channels and is found to be close to that obtained with a nonblind receiver.

Downlink beamforming for spatially distributed sources in cellular mobile communications

This paper presents a new technique for downlink transmission beamformer design in cellular mobile communication systems using antenna arrays at the base station. The method is based on estimation of an underlying spatial distribution associated with each source’s spatial downlink channel. The algorithm is ‘blind’ in the sense that it depends only on uplink spatial channel statistics, requiring no mobile-to-base station feedback in the design procedure. The assumed underlying spatial distribution models are general enough to be used in a wide variety of mobile communications scenarios (e.g., rural, urban, sub-urban, indoor). The technique is of reasonable complexity with a significant portion of the computation carried out off-line. Simulation results verify the effectiveness of the approach.

Capacity results of spatially correlated frequency-selective MIMO channels in UMTS

Multi-input multi-output (MIMO) channels arising from the use of multi-element antenna (MEA) systems both in transmission and reception have been shown to support a considerable amount of bit rate. The information-theoretic capacity of such channels is severely affected by the spatial correlation. In this paper, we evaluate the ergodic and outage capacity of typical MIMO channels appearing in UMTS indoor scenarios. The frequency-selectivity and the spatial correlation of the MIMO channel are taken into account using realistic models obtained from field measurements performed within the IST project METRA (http://www.ist-metra.org). For capacity assessment, we use the transmission schemes considered by the 3GPP for UMTS. In particular, we analyze the cases of having and not having channel state information (CSI) at the transmitter, and also the case in which beamforming is used for transmission.

The IST METRA project

This article summarizes the main achievements of the Multi-Element Transmit and Receive Antennas (METRA) Project, an IST research and technological development project carried out between January 2000 and June 2001 by Universitat Politecnica de Catalunya, the Center for Personkommunikation of Aalborg University, Nokia Networks, Nokia Mobile Phones, and Vodafone Group Research and Development. The main objective of METRA was the performance evaluation of multi-antenna terminals in combination with adaptive antennas at the base station in UMTS communication systems. A MIMO channel sounder was developed that provided realistic multi-antenna channel measurements. Using these measured data, stochastic channel models were developed and properly validated. These models were also evaluated in order to estimate their corresponding channel capacity. Different MIMO configurations and processing schemes were developed for both the FDD and TDD modes of UTRA, and their link performance was assessed. Performance evaluation was completed by system simulations that illustrated the benefits of MIMO configurations to the network operator. Implementation cost vs. performance improvement was also covered by the project, including the base station and terminal manufacturer and network operator viewpoints. Finally, significant standards contributions were generated by the project and presented to the pertinent 3GPP working groups.

Blind multiuser identification and detection in CDMA systems

Multiuser detection in code division multiple access systems usually requires either knowledge of the transmitted signature sequences and channel state information or use of a known training sequence for adaptation. We develop a scheme that can be employed for the joint adaptive blind multiuser identification and detection in asynchronous CDMA systems. This scheme relies on a multiuser Viterbi algorithm that incorporates an adaptive estimation of the overall channel impulse responses, given by the convolution of the signature sequences of the users and corresponding physical channels impulse responses. Once the overall channel responses are estimated, the blind multiuser detection algorithm performs like the maximum-likelihood sequence estimator. Results are provided to illustrate the convergence of the blind multiuser approach, near-far resistance and sensitivity to the algorithm initialization.

Smart antennas in software radio base stations

The application of adaptive antenna techniques to fixed-architecture base stations has been shown to offer wide-ranging benefits, including interference rejection capabilities or increased coverage and spectral efficiency. Unfortunately, the actual implementation of these techniques to mobile communication scenarios has traditionally been set back by two fundamental reasons. On one hand, the lack of flexibility of current transceiver architectures does not allow for the introduction of advanced add-on functionalities. On the other hand, the often oversimplified models for the spatiotemporal characteristics of the radio communications channel generally give rise to performance predictions that are, in practice, too optimistic. The advent of software radio architectures represents a big step toward the introduction of advanced receive/transmit capabilities. Thanks to their inherent flexibility and robustness, software radio architectures are the appropriate enabling technology for the implementation of array processing techniques. Moreover, given the exponential progression of communication standards in coexistence and their constant evolution, software reconfigurability will probably soon become the only cost-efficient alternative for the transceiver upgrade. This article analyzes the requirements for the introduction of software radio techniques and array processing architectures in multistandard scenarios. It basically summarizes the conclusions and results obtained within the ACTS project SUNBEAM, proposing algorithms and analyzing the feasibility of implementation of innovative and software-reconfigurable array processing architectures in multistandard settings.

Day-ahead bidding strategies for demand-side expected cost minimization

Day-ahead DSM techniques in the smart grid allow the supply-side to know in advance an estimation of the amount of energy to be provided to the demand-side during the upcoming day. However, a pure day-ahead optimization process cannot accommodate potential real-time deviations from the expected energy consumption by the demand-side users, neither the randomness of their renewable sources. This paper proposes a day-ahead bidding system based on a pricing model that combines: i) a price per unit of energy depending on the day-ahead bid energy needs of the demand-side users, and ii) a penalty system that limits the real-time fluctuations around the bid energy loads. In this day-ahead bidding process, demand-side users, possibly having energy production and storage capabilities, are interested in minimizing their expected monetary expense. The resulting optimization problem is formulated as a noncooperative game and is solved by means of suitable distributed algorithms. Finally, the proposed procedure is tested in a realistic setup.

Optimal Resource Allocation in Relay-Assisted Cellular Networks With Partial CSI

Emerging cellular networks are likely to handle users with heterogeneous quality of service requirements attending to the nature of their underlying service application, the quality of their wireless equipment, or even their contract terms. While sharing the same physical resources (power, bandwidth, transmission time), the utility they get from using them may be very different and arbitrage is needed to optimize the global operation of the network. In this respect, resource allocation strategies maximizing network utility under practical constraints are investigated in this paper. In particular, we focus on a cellular network with half-duplex, MIMO terminals and relaying infrastructure in the form of fixed and dedicated relay stations. Whereas orthogonal-frequency-division multiple access is assumed, it is seen as a frequency diversity enabler since path loss is the only channel state information (CSI) known at the transmitters, which is refreshed periodically. With this setup, the performance of a state-of-the art relay-assisted transmission protocol is characterized in terms of the ergodic achievable rates, for which novel concave lower bounds are developed. The use of these bounds allows us to derive two efficient algorithms computing resource allocations in polynomial time, which address the optimization of the uplink and downlink directions jointly. First, a global optimization algorithm providing one Pareto optimal solution maximizing network utility during the validity period of one CSI is studied, which acts as a performance upper bound. Second, a sequential optimization algorithm maximizing network utility frame by frame is considered as a simpler alternative. The performance of both schemes has been compared in practical scenarios, giving special attention to the performance-complexity and throughput-fairness tradeoffs.