This paper provides useful insights into the practical design of bit allocation algorithms in multiantenna multiuser orthogonal frequency-division multiplexing (OFDM) systems. With the degrees of freedom obtained with multiple antennas and multiple subcarriers, the performance might be enhanced at the expense of a higher complexity. Since the scheduling with realistic integer mappings is an NP-complete combinatorial problem, suboptimum solutions based on the scalar product are shown to be good candidates for yielding a realizable scheduler at a wireless physical layer. Additionally, a power reuse strategy is proposed to lower the computational requirements of such a system. Besides the tradeoff between performance and complexity, there exists the tradeoff between performance and signaling. Therefore, we show that the required signaling might be reduced either by a user-subcarrier clustering or by using a scheme that forces an equal mapping for all the users at the same subcarrier, which might be well-suited if instantaneous fairness is required. The proposed strategies are evaluated for typical OFDM-based wireless LAN scenarios.

Motivated by the theoretical results on multi-antenna signal processing techniques promising substantial performance gains, a feasible reconfigurable hardware architecture for OFDM-based Wireless LANs is presented in this paper. The ultimate objective of the platform is to support single-antenna links, as well as antenna arrays at the receiver and/or at the transmitter, taking into account the limitations caused by a real-time implementation. After a brief overview of the implemented multi-antenna algorithms, we present the hardware platform that has been built based on both fixed point and floating point DSPs from Texas Instruments, together with the evaluation of the complexity associated to the operations, and their scheduling. The performance indicates that a multi-antenna architecture supporting up to four antennas at the receiver side might accomplish the real-time requirements.

Given a zero forcing transmit beamforming, we focus on how the multi-antenna access point distributes the scarce resource (power) among the single-antenna terminals. Since there is a clear trade-off between the satisfaction of the individual needs and the global performance of the cell, several criteria are proposed, ranging from a classical physical layer point of view of capacity (rate) maximization to bit error rate (BER)-based cost functions, which are closer to the second layer of the protocol stack. Between two traditional techniques, namely the uniform power allocation and the equal BER and rate, a new one is proposed, which ultimately provides an intermediate performance. Then, we add BER (or signal to noise ratio) constraints so that the admission control problem has to be solved. Among traditional options, we propose a new mechanism to balance the above-mentioned trade-off between the total performance and the particular user behavior. The results in terms of fairness are presented by a mean vs. variance plot and by the Gini plot.

In multi-user communications, the access point (AP) has several alternatives for distributing the scarce resources among users. Since there exists a trade-off between the global performance and the individual needs, an analytical framework to study fairness is derived, which completes the scope given by the existing fairness indexes in the literature. The framework proposed in this paper is a way to interpret fairness that has been inspired by portfolio selection; basically, it analyzes the mean vs. standard deviation trade-off. In this work, the target application is a multi-antenna AP transmitting simultaneously to several single-antenna terminals, although this framework is valid to analyze other procedures in multi-user communications.

In this paper, we address the problem of transmit beamforming, power allocation, bit loading, and admission control in a multi-user scenario, where several single antenna mobile terminals are served by one base station equipped with an antenna array. In particular, we explore the impact of using either optimal or zero-forcing transmit beamforming schemes in combination with different bit allocation strategies, namely the maximization of the sum rate (MSR), the maximization of the minimum rate (MMR) and a modified version of the latter, for a finite set of modulation schemes. The performance evaluation is conducted by means of system-level simulations, using a realistic channel model for urban micro cells, with an emphasis not only on the aggregated cell throughput but also on the associated fairness issues

Motivated by the extensive use of game-theoretic strategies for uplink power control in CDMA, we compare in this paper a strategy based on the widespread utility function used in the literature with other traditional schemes based on the BER. Here, we focus on the downlink of a communication system. Basically, that utility function is a ratio between the frame success rate and the used power. It is shown in this paper that the strategy maximizing the utility implies a higher error rate than for other classical schemes, which was not shown in the literature to the best of our knowledge. Finally, we briefly discuss the usefulness of pricing mechanisms in a game-theoretic formulation of the power control.

At a multi-antenna base station, the multiple antennas are used to enhance the scheduling task. After applying a zero forcing transmit beamforming, the scheduling distributes the resources among the users. Several criteria are presented and their performance in the high signal-to-noise ratio (SNR) range is analyzed. The next issue is to take into account the SNR requirements from the users and perform admission control accordingly. An algorithm that yields the optimum performance is proposed, together with a new criterion that falls between the optimization of the best global performance and the satisfaction of the individual needs. Simulation results are provided to show the performance of the techniques.

This paper deals with practical multiantenna multiuser OFDM systems. With the additional degrees of freedom of multiple antennas and multiple subcarriers, the performance might be enhanced, but the scheduling complexity might increase exponentially. Since the scheduling with realistic integer signal mappings is an NP-complete combinatorial problem, suboptimum solutions based on the scalar product are good candidates to yield a fast and realizable practical implementation. We propose afterwards a power reuse strategy to lower the computational complexity and show that the amount of signaling can be reduced by forcing an equal mapping for all the users at the same subcarrier.

In a multi-antenna broadcast channel, the access point (AP) has several alternatives for distributing the scarce resources among the users. When realistic conditions are taken into account, it is not clear which is the best suited option for the AP, since there exist a trade-off between the global performance and the individual needs. In this paper, we derive an analytical framework to study fairness in a multi-antenna multi-user channel, which is useful in practical situations. Since fairness indexes in the literature usually reflect relative performance among users, we borrow ideas from portfolio selection and propose a mean versus standard deviation analysis that allows us to select a certain technique under practical conditions. We particularize this framework for a multi-antenna AP communicating simultaneously with several single-antenna terminals, and give closed-form expressions for the mean versus standard deviation trade-off for zero forcing beamforming, dirty paper encoding, and the cooperative bound, under the assumption of a uniform power allocation among the active users. This framework can be extended to analyze other types of multi-user communications.

This paper studies the application of the minimum mean square error (MMSE) beamformer to orthogonal frequency division multiplexing (OFDM)-based wireless local area networks. The questions here addressed are mainly the design with finite-length data and the choice of the OFDM signal domain where the beamformer is applied, either frequency or time. As OFDM signals need more samples than other modulations to stabilize the estimation of the signal statistics, how to exploit the finite-length training sequence provided for the design of equalizers becomes an important issue. The paper also shows that the usual frequency processing in OFDM is not always the best choice for the spatial beamforming, mainly for channels with a very high delay spread. Then, time processing turns out to be the best suited approach in terms of the tradeoff between performance and complexity. Additionally, novel modifications of the MMSE spatial filter are proposed to improve the raw bit-error rate performance: 1) a temporal semiblind approach that exploits the cyclic prefix and 2) windowing in the frequency domain.

This paper deals with the spatio-temporal scheduling of a set of users for downlink transmission in a cell where the base station is provided with multiple antennas. Two main issues are addressed: how the users are distributed into space-time groups and how the available power is allocated among the users within a group. Since the former is an NP-complete combinatorial problem, we develop fast and low-complexity algorithms, which might be capable to fulfill the real-time requirements of a practical scheduling scheme. Regarding the power allocation, we consider different fairness criteria under the capacity point of view. To be precise, we compare the alternatives of equal rate and maximum sum rate with our proposed novel equal proportional rate solution.

This paper deals with the translation into a practical hardware design of antenna array algorithms developed especially for the European Wireless LAN standard Hiperlan/2 (HL2). The ultimate goal is to demonstrate the feasibility of Multi Element Antenna (MEA) systems with current available hardware. Whereas optimality is the key point in the theoretical analysis of techniques, practical details play the main roles in hardware integration. Here, we describe both the optimum techniques based on theoretical studies and related practical concerns about those algorithms. We show that optimum performances are not always attainable in realistic hardware design.

Adaptive antenna arrays can be used to improve the performance of Orthogonal Frequency Division Multiplexing systems. They are usually applied in the frequency domain, after the FFT demodulation. In this paper, the selected algorithms are applied in time domain. A blind method is firstly proposed for the maximization of the temporal Signal to Noise plus Interference Ratio (SNIR) in frequency selective channels exploiting the temporal redundancy introduced by the cyclic prefix (CP). This algorithm may cope well with non-stationary interference that appears during the burst transmission. This blind technique is extended so as to take advantage of the preamble that precedes the useful data in the HIPERLAN/2 (HL/2) specification, Simulations show that this latter semiblind approach improves the overall performance of the system with respect to the traditional Sample Matrix Inversion (SMI) algorithm even in interference stationary scenarios. Additionally, a moving pilot structure is proposed to perform more accurate channel estimation, which further improves the performance of the semiblind technique.

Blind and semiblind antenna array algorithms are proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems in the time domain. A blind technique is proposed for the maximization of the temporal Signal to Noise plus Interference Ratio (SNIR) in frequency-selective channels exploiting the Cyclic Prefix (CP). In OFDM systems, this maximization does not imply the minimization of the Bit Error Rate (BER). Thus, a semiblind method that takes advantage of both known training data and the CP is obtained, which provides the best results in terms of link quality. Simulations are conducted for Hiperlan/2 (HL/2) parameters, and a slight modification of its fixed pilot position is proposed, so as to improve the BER performance of the algorithms and to obtain estimates of the channel for the blind method.

In this paper, we deal with the problem of the multi-antenna array receiver optimization for OFDM-based wireless LANs. In fact, it has been stated that the best algorithm and even its key parameters depend deeply on the working environment. For these choices, two solutions are here proposed: the classical bayesian channel classification and a fuzzy inference-based selection for a single antenna. After that, we exploit the receiver spatial diversity by using a Fuzzy Logic System (FLS). Conducted simulations show that the performance of the fuzzy inference-based classifiers can reach the optimum bayesian results at good SINR, while the proposed FLS exploits successfully the array at reception when the errors of the single antenna classifier are over a certain threshold.

The performance of very high data rate wireless local area networks (WLAN) is degraded by several problems such as long delay spread in outdoor environments or interference that may arise both from other WLAN or from other systems sharing the same band. The current standards allow the use of multiple antennas at the receiver in a single input multiple output (SIMO) configuration. Traditionally, algorithms have been applied in the frequency domain, but this paper presents a comparison of three approaches to be applied also in the time domain. It is shown that a significant uncoiled bit error rate (BER) performance improvement can be achieved by working before the FFT at the receiver side, especially for channels with large delay spreads.

The sample matrix inversion (SMI) algorithm has been widely applied in the filed of adaptive antenna arrays. However, in time division multiple access (TDMA) systems with known data sequences, a low cost solution would imply the computation of the beamformer based exclusively on this data. In some cases, this might not be possible since the known data could not be sufficient to get a stable estimate of both the sample covariance matrix and the steering vector needed for the SMI spatial filter. In this paper, windowing techniques are applied in order to calculate a beamformer per subcarrier for orthogonal frequency division multiplexing (OFDM) systems with very limited known training. This approach is compared to the subcarrier grouping approach, and the presented results show that the former method provides a further performance gain, even in channels with high delay spread.