Angel Lozano’s research while affiliated with Pompeu Fabra University and other places

Using multiple antennas at both the transmitter and receiver, BLAST exploits the multipath characteristics of a wireless channel to enable very large capacities. In an extended V-BLAST, those capacities are approached with single-dimensional coding and rate adaptation. However, such results require infinite precision for rate and power, which is not implementable due to a limited data rate on the feedback channel. We show that discretizing the rates to QAM constellations causes a 3-5 dB penalty. We then propose SQPC (successive quantization with power control), an ad-hoc low-complexity algorithm that reduces that penalty to 1-3 dB. We show that SQPC closely approaches the performance limit attainable with discrete QAM rates, which we find numerically by exhaustive search

Previous results in information theory have demonstrated the enormous capacity potential of wireless communication systems with antenna arrays at both the transmitter and receiver. To exploit this potential, the Bell-laboratories LAyered Space-Time (BLAST) architecture was proposed. BLAST systems transmit parallel data streams, simultaneously and on the same frequency, in a Multiple-Input Multiple-Output (MIMO) fashion. With rich multipath propagation, these different streams can be separated and recovered at the receiver. The analysis of BLAST presented thus far had always been strictly narrowband. In this paper, we extend the formulation by presenting a receiver devised for more general frequency-selective channels. This new receiver is evaluated-via simulation-in the context of a typical urban (TU) channel with excellent results

Previous results in information theory have demonstrated the enormous capacity potential of wireless communication systems with multiple transmit and receive antennas. To exploit this potential, the Bell-laboratories LAyered Space-Time (BLAST) architecture was proposed. BLAST systems transmit parallel data streams, simultaneously and on the same frequency, in a multiple-input multiple-output fashion. With sufficient multipath propagation, these different streams can be separated at the receiver. The link performance of BLAST has been thoroughly studied, but always in the presence of the spatially white noise. However, in the context of a multiple-access system, the dominant impairment is usually co-channel interference that is-in general-spatially colored. We present a generalization of BLAST that is optimal, in the sense of maximizing the link spectral efficiency, in the presence of spatially colored interference. In this general scheme, the channel and interference covariance are made available to the transmitter, which finds the channel eigenmodes in the presence of the interference and sends multiple data streams through those eigenmodes. We evaluate the spectral efficiency of this new architecture and compare it, under various propagation conditions, to other forms of BLAST in order to quantify the value of providing interference information to the transmitter. Furthermore, the new scheme is also compared to other adaptive-array techniques with equal number of antennas

Recent information-theory results have shown the enormous capacity potential of wireless techniques that use transmit and receive antenna arrays. As a result, a number of layered space-time (BLAST) architectures have been proposed wherein multiple data streams are transmitted in parallel and separated at the receiver on account of their distinct spatial signatures. While extremely promising, all analysis of BLAST to date were restricted to the context of a single-user link. In this paper, the system-level benefit of using BLAST in multicell scenarios is evaluated in comparison with other directive- and adaptive-array techniques

Multiple antennas and space-time processing are known to provide large link-level capacity gains. In this paper we investigate the system-level impact of using antenna arrays with up to four elements at both transmitter and receiver in a downlink CDMA system. We consider the following uses for multiple transmit antennas: transmit diversity, BLAST transmission (using the same spreading code to radiate independent data from different antennas), and directive beam steering. Link spectral efficiencies can be calculated as a function of the required signal-to-interference ratio (SIR) assuming capacity-approaching channel coding. System-level simulations provide the probability distribution of received SIR in a multi-cell CDMA system, with and without directive beam steering. The link- and system-level results are then combined to yield the number of equal-rate users that can be supported at some outage level. We show that 10 fold increases in user capacity can be achieved when up to four antenna elements are used on each side of the link (assuming a per-user rate of 1.25 Mbps and a 5-MHz bandwidth)

In BLAST (Bell-Laboratories LAyered Space Time) systems, multiple transmit and receive antennas are employed to achieve very high spectral efficiencies. The ideal detection method for such systems is the maximum-likelihood (ML) algorithm. However, the ML complexity increases exponentially with the number of transmit antennas and the number of bits per modulation symbol. A reduced-complexity detection method has been suggested, using ordered successive interference cancellation. We consider two other suboptimum techniques: channel-based adaptive group detection and multistep reduced-constellation detection. The goal is to reduce the two aforementioned complexity exponentials. The algorithms efficiently combine linear processing with local ML search. We limit the complexity by maintaining small ML searching areas, while maximizing the performance under the complexity constraint by optimizing the front-end linear processing and the selection of the search areas

With the evolution of analog mobile wireless communications systems into digital second- and third-generation systems, there is growing interest in finding more efficient ways of managing the available resources, in particular radio spectrum and power. In the context of time division multiple access (TDMA) systems, this interest has led to the development of a variety of dynamic channel assignment (DCA) and power control (PC) algorithms. Despite the intense activity in both the DCA and the PC arenas and some proposals for combined DCA with PC, not enough work has been devoted to effectively integrating them. In this paper, the integration of DCA and PC is investigated and a family of integrated algorithms is presented. These algorithms, fully distributed and cost adaptive, achieve capacity levels significantly higher than those of a system with only DCA or PC. With respect to a system without any DCA or PC, several-fold capacity increases are obtained. Furthermore, these capacity levels are attained with user mobility included in the analysis

An important aspect of any channel assignment algorithm should be balancing the performance of uplink and downlink. Differences in receiver performance, diversity and transmit power used at mobiles and base stations are potential sources of imbalance. In addition, there is a fundamental asymmetry between uplink and downlink interference caused by the locations of mobiles and base stations. We investigate the nature of this asymmetry and prove that the uplink frequently has worse interference. Furthermore, this difference shows little dependence on the degree of mobility and is basically associated with the location of mobiles rather than their speed