Matteo Trivellato

Increasing downlink cellular throughput with limited network MIMO coordination

Single-user, multiuser, and network MIMO performance is evaluated for downlink cellular networks with 12 antennas per site, sectorization, universal frequency reuse, scheduled packet-data, and a dense population of stationary users. Compared to a single-user MIMO baseline system with 3 sectors per site, network MIMO coordination is found to increase throughput by a factor of 1.8 with intra-site coordination among antennas belonging to the same cell site. Intra-site coordination performs almost as well as a highly sectorized system with 12 sectors per site. Increasing the coordination cluster size from 1 to 7 sites increases the throughput gain factor to 2.5.

On transceiver design and channel quantization for downlink multiuser MIMO systems with limited feedback

We consider a MIMO broadcast channel where both the transmitter and receivers are equipped with multiple antennas. Channel state information at the transmitter (CSIT) is obtained through limited (i.e., finite-bandwidth) feedback from the receivers that index a set of precoding vectors contained in a predefined codebook. We propose a novel transceiver architecture based on zero-forcing beamforming and linear receiver combining. The receiver combining and quantization for CSIT feedback are jointly designed in order to maximize the expected SINR for each user. We provide an analytic characterization of the achievable throughput in the case of many users and show how additional receive antennas or higher multiuser diversity can reduce the required feedback rate to achieve a target throughput.We also propose a design methodology for generating codebooks tailored for arbitrary spatial correlation statistics. The resulting codebooks have a tree structure that can be utilized in time-correlated MIMO channels to significantly reduce feedback overhead. Simulation results show the effectiveness of the overall transceiver design strategy and codebook design methodology compared to prior techniques in a variety of correlation environments.

User Selection Schemes for MIMO Broadcast Channels with Limited Feedback

We propose a user selection algorithm and the supporting feedback scheme, for MIMO Gaussian broadcast channels with arbitrary number of users, transmit beamforming and limited channel state information (CSI) available at the transmitter. The method relies on estimation of the user signal-to-interference-plus-noise ratios (SINRs) at the transmitter, by means of an appropriate finite-rate channel report from the mobiles. The basic principle is that users are added successively only if they are beneficial to the system in terms of increased throughput. Numerical results show improved performance compared to other finite-rate feedback schemes.

Multiuser eigenmode transmission for mimo broadcast channels with limited feedback

We consider the problem of communicating in a MIMO broadcast channel (a point-to-multipoint system where both the transmitter and receivers employ multiple antennas) where the transmitter has imperfect knowledge of the MIMO channels due to limited feedback from the receivers. Our proposal is based on a low-complexity technique known as multiuser eigenmode transmission (MET) which has been shown to achieve near-optimum performance using a zero-forcing type of beamforming under perfect channel state information at transmitter. In the case of limited feedback, each user receives residual interbeam interference, and we propose to mitigate its effect at each receiver with spatial MMSE processing. We compare the sum rate performance of the proposed MET with partial channel state information (CSI) technique with a baseline and with the ideal MET that has perfect channel knowledge at the transmitter. We show that the proposal provides performance gains over the baseline for a moderate number of feedback bits and differently from the baseline, when the feedback rate increases, it approaches the ideal MET sum rate over the entire range of SNR conditions considered.

State control in networked control systems under packet drops and limited transmission bandwidth

The widespread proliferation of wireless sensor networks is revolutionizing our capabilities of monitoring and controlling the environment. The wireless connection of spatially distributed sensors, controllers and actuators poses challenges to the control system, due to packet drops, delays and measurements quantization, as well as to the wireless network resource allocator. These challenges push for a cross-layer design of communication and estimation/control systems. In this paper, assuming a TCP-like protocol between controller and actuator, we solve the problem of optimum control around a target state for a stable system in case of both packet drops and signal quantization. Generalization for unstable systems is also given in case of negligible quantization error. Moreover we propose a general framework for cross-layer optimization of signal quantization and network resource allocation. Here our main contributions are on i) quantizer design (how many bits to allocate for signal quantization), ii) network resource allocation (bit-rate for each radio link) and iii) choice of the transmission mode (constellation and channel coding rate). As application example, we consider a simple scalar, stable system and compare network resource allocation in the presence of i) low-cost sensors using a fix modulation and ii) long-term future sensors capable of rate adaptation. Interestingly, almost optimal control is achievable with small bandwidth transmissions and simple BPSK, supporting the use of low-cost sensors in applications dealing with state control around a target state trajectory.

Performance of multiuser MIMO and network coordination in downlink cellular networks

We consider a wireless network with multiple cells where base stations with multiple antennas transmit to multiple users, each with multiple antennas. Using single-user (SU) MIMO as a baseline, we evaluate the system throughput performance of multiuser (MU) MIMO with generalized zero-forcing beamforming under a multiuser proportional fair scheduling metric. We consider network MIMO extensions of this technique by coordinating transmission among clusters of spatially distributed bases. By significantly mitigating intercell interference, network MIMO provides a tradeoff between improved performance and increased backhaul complexity that depends on the coordination cluster size. We describe a general technique for simulating cellular networks that is applicable to next-generation packet-based cellular standards, and we evaluate the performance of MU and network MIMO in heavily loaded networks. Compared to the SU MIMO baseline, median system throughput can be doubled by coordinating MU MIMO transmission among clusters of 3 adjacent cells.

On channel quantization and feedback strategies for multiuser MIMO-OFDM downlink systems

We consider a multiuser MIMO-OFDM downlink system with single antenna mobile terminals (MTs) where channel state information at the base station is provided through limited uplink feedback (FB). In order to reduce the FB rate and signal processing complexity, the available bandwidth is divided into resource blocks (RBs) whose number of subcarriers reflects the coherence bandwidth of the channel. This approach is very common in the standardization of 4th generation wireless communication systems and justifies an independent channel quantization per RB. Within this framework the paper contains two main contributions. Firstly we provide joint conditions on the channel coherence bandwidth and the FB rate per RB that allow for a simpler quantization of the RB channel matrix (space-frequency) by a space vector, causing negligible performance loss in terms of system achievable throughput. This is accomplished after deriving a new metric for codebook design in RB channel quantization that exploits spatial and frequency correlation. As a second contribution we investigate the trade-off between accurate channel knowledge and frequency/multiuser diversity. It is seen that even for a moderate number of MTs in the network, concentrating all the available FB bits in characterizing only one RB provides a significant gain in system throughput over a more classical distributed approach and this result is validated both analytically and by simulations.

Zero-forcing vs unitary beamforming in multiuser MIMO systems with limited feedback

We consider a multiuser MIMO downlink system with multiple antenna mobile terminals where channel state information at the base station is provided through limited uplink feedback. In a multi-cell environment we compare two transceiver architectures based on zero forcing and unitary beamforming respectively. For both schemes we show how the additional degrees of freedom provided by multiple receive antennas can be exploited to improve system performance, by a proper design of the receive combiner. We propose channel quantization solutions that adapt to the transceiver architectures and exploit MIMO channel statistic. Numerical simulations validate the effectiveness of the proposals in a multi-cell environment where long-term proportional fairness is guaranteed among the users in the network.

Predictive Channel Quantization and Beamformer Design for MIMO-BC with Limited Feedback

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.

Antenna Combining and Codebook Design for the MIMO Broadcast Channel with Limited Feedback

We consider a MIMO broadcast channel where both the transmitter and receivers are equipped with multiple antennas and where channel state information at the transmitter (CSIT) is provided through limited (i.e., finite-bandwidth) feedback from the receivers. Adopting a simple zero-forcing type of beamformer, we show how additional degrees of freedom provided by multiple antennas at the receiver can be exploited to improve system performance. We propose a new solution where the linear receiver and the channel quantization for CSIT feedback are jointly designed in order to maximize the expected SINR for each user. Based on a modified Lloyd-Max algorithm, the proposed channel quantization technique uses empirical channel realizations drawn from channel statistics, creating tailored codebooks suited for any antenna configuration or environment. The resulting codebook also has a tree structure that can be utilized in time-correlated MIMO channels to reduce feedback overhead. Simulation results show the effectiveness of the overall transceiver design strategy compared to prior techniques in a variety of correlation environments.