We consider a cellular system using frequency division duplexing and orthogonal frequency division multiplexing (OFDM), where the base station has multiple antennas and each mobile terminal feeds back a quantized version of the channel state information. For downlink transmission, the base station performs joint scheduling and beamforming with the objective of maximizing the system throughput. In this letter, we propose an iterative (in the user selection) beamforming algorithm which exploits approximated orthogonality conditions of the scheduled users. By simulation results it is seen that new approach outperforms existing scheduling techniques in terms of outage throughput with similar or lower complexity.

We consider a multiuser downlink transmission from a base station with multiple antennas (MIMO) to mobile terminals (users) with a single antenna, using orthogonal frequency division multiplexing (OFDM). Channel conditions are reported by a feedback from users with limited rate, and the base station schedules transmissions and beamforms signals to users. We show that an important set of schedulers using a general utility function can be reduced to a scheduler maximizing the weighted sum rate of the system. For this case we then focus on scheduling methods with many users and OFDM subcarriers. Various scheduling strategies are compared in terms of achieved throughput and computational complexity and a good tradeoff is identified in greedy and semiorthogonal user selection algorithms. In the greedy selection algorithm, users are selected one by one as long as the throughput increases, while in the semiorthogonal approach users are selected based on the channel correlation. An extension of these approaches from a flat-fading channel to OFDM is considered and simplifications that may be useful for a large number of subcarriers are presented. Results are reported for a typical cellular transmission of the long-term evolution (LTE) of 3GPP.

The real time estimation of the period of signals that are periodic over short time intervals requires fast algorithms. In this letter, the maximum likelihood (ML) period estimator is derived for a periodic signal with additive white Gaussian noise. A low complexity approximation is then proposed, and compared with the state of the art of the estimation techniques in a practical scenario for the remote estimation of human heart rate using an ultra wide band radar.

Ultra Wide Band radar is a promising technique for remote vital signs monitoring. For home monitoring and consumer devices, FFC rules pose severe limits to the available band and the maximum transmitted power. In this paper vital signs (heartbeat and respiration rate) are monitored with a FCC compliant system; in this scenario, time of arrival variations are not sufficient to detect vital signs. Therefore, amplitude and phase modulation is investigated; both theoretical analysis and experimental results show that vital signs affect both the amplitude and the phase modulation.

In a cellular system with partial channel state information, i.e. with limited feedback, and multiple antennas, we consider scheduling of downlink transmissions at the base station using beamforming and orthogonal frequency division multiplexing. As the complexity of optimal scheduling for throughput maximization under quality of service constraints grows exponentially with the number of subcarriers, in this paper we propose two low complexity suboptimal techniques. The first is a greedy iterative strategy that at each step selects one user with the aim of maximizing the weighted sum rate (WSR), without the need of recomputing the beamformer. We next propose a pre-selection strategy that removes from the selection process users that do not provide an increase in the WSR, thus speeding the search. Both complexity and performance of the proposed techniques are evaluated and compared with existing solutions in a long-term evolution 3GPP scenario.

For a frequency division duplexing (FDD) cellular system, the downlink channel state information (CSI) has to be fed back by mobile terminals (MTs) in order to perform beamforming and scheduling at base station (BS). In this paper, for an orthogonal frequency division multiplexing (OFDM) modulation format, we propose a novel CSI feedback strategy based on the prediction of channel variations. Indeed, quantization of CSI and feedback signalling are jointly designed in order to obtain a low rate feedback signal. Also, an user selection method is devised to allocate users across the subcarriers. Simulations for a 3G long term evolution scenario show a significant performance improvement achieved by the predictive strategy with respect to existing techniques.

For a cellular system based on frequency division duplexing where the base station (BS) is equipped with multiple antennas and the mobile terminals (MTs) have one antenna each, we propose joint techniques to a) feed back channel state information from MTs to the BS, b) design the beamformer and c) schedule downlink transmissions. We propose that both BS and MT predict channel variations, and the feedback (FB) information from MT to BS is given by the prediction error. For the beamformer design we both consider a zero forcing approach and investigate a new solution based on the minimum mean square error criterion, which takes into account the quantization error. By exploiting the FB information, we derive approximated expressions of the signal to noise ratio relative to each MT, used at BS to perform scheduling with an efficient greedy algorithm. Performance assessment on realistic 3GPP channel models show that the proposed techniques provide a significant improvement of the network throughput at a lower FB rate than existing solutions.

For the downlink of a wireless cellular system where the base station (BS) uses multiple antennas in a beamforming configuration for a multiuser transmission (broadcasting), we investigate two techniques for quantizing the channel state information at the mobile terminal and feeding it back to the BS. In both cases quantization of channel vectors and feedback signaling are jointly designed in order to obtain a low-rate feedback (FB). In particular, we first consider a tree structure vector quantizer (VQ) of the channel vector with a novel metric, as an alternative to the classical mean square error. It is seen that the tree search allows to lower the FB signaling rate also in a time-varying environment. As an alternative, a predictive VQ is proposed. These two and other FB strategies were extensively compared in a typical cellular environment for different mobile speeds and FB rates.