On the Required Number of Antennas in a Point-to-Point Large-but-Finite MIMO System: Outage-Limited Scenario

This paper investigates the performance of the point-to-point multiple-input-multiple-output (MIMO) systems in the presence of a large but finite numbers of antennas at the transmitters and/or receivers. Considering the cases with and without hybrid automatic repeat request (HARQ) feedback, we determine the minimum numbers of the transmit/receive antennas which are required to satisfy different outage probability constraints. Our results are obtained for different fading conditions and the effect of the power amplifiers efficiency on the performance of the MIMO-HARQ systems is analyzed. Moreover, we derive closed-form expressions for the asymptotic performance of the MIMO-HARQ systems when the number of antennas increases. Our analytical and numerical results show that different outage requirements can be satisfied with relatively few transmit/receive antennas.Comment: Under review in IEEE Transactions on Communication

Precoded Integer-Forcing Universally Achieves the MIMO Capacity to Within a Constant Gap

An open-loop single-user multiple-input multiple-output communication scheme is considered where a transmitter, equipped with multiple antennas, encodes the data into independent streams all taken from the same linear code. The coded streams are then linearly precoded using the encoding matrix of a perfect linear dispersion space-time code. At the receiver side, integer-forcing equalization is applied, followed by standard single-stream decoding. It is shown that this communication architecture achieves the capacity of any Gaussian multiple-input multiple-output channel up to a gap that depends only on the number of transmit antennas.Comment: to appear in the IEEE Transactions on Information Theor

Advanced wireless communications using large numbers of transmit antennas and receive nodes

The concept of deploying a large number of antennas at the base station, often called massive multiple-input multiple-output (MIMO), has drawn considerable interest because of its potential ability to revolutionize current wireless communication systems. Most literature on massive MIMO systems assumes time division duplexing (TDD), although frequency division duplexing (FDD) dominates current cellular systems. Due to the large number of transmit antennas at the base station, currently standardized approaches would require a large percentage of the precious downlink and uplink resources in FDD massive MIMO be used for training signal transmissions and channel state information (CSI) feedback. First, we propose practical open-loop and closed-loop training frameworks to reduce the overhead of the downlink training phase. We then discuss efficient CSI quantization techniques using a trellis search. The proposed CSI quantization techniques can be implemented with a complexity that only grows linearly with the number of transmit antennas while the performance is close to the optimal case. We also analyze distributed reception using a large number of geographically separated nodes, a scenario that may become popular with the emergence of the Internet of Things. For distributed reception, we first propose coded distributed diversity to minimize the symbol error probability at the fusion center when the transmitter is equipped with a single antenna. Then we develop efficient receivers at the fusion center using minimal processing overhead at the receive nodes when the transmitter with multiple transmit antennas sends multiple symbols simultaneously using spatial multiplexing

Analysis and Design of Line of Sight MIMO transmission systems

A cost-effective solution to the problem of guaranteeing backhaul connectivity in mobile cellular networks is the use of point-to-point microwave links in the Q-Band and E-Band. The always increasing rate in mobile data traffic makes these microwave radio links a potential bottleneck in the deployment of high-throughput cellular networks. A fundamental way to characterize the impact of phase noise on the throughput of these systems is to study their Shannon capacity. Unfortunately, the capacity of the phase-noise channel is not known in closed-form, even for simple channel models. The effect of phase noise in telecommunication systems is more evident in presence of multiple antennas at transmitter and receiver because of the overlapping of phase noise contribution in receivers. We propose a simulated-based tool to compute a lower bound to channel capacity for SISO and MIMO systems in presence of phase noise with one oscillator shared among the antennas per side and we give a non asymptotic expression of an upper bound to capacity always for SISO and MIMO channels. Finally we present a low complex phase detector based on combination of Phase Locked Loop (PLL) exploiting the decisions made by a turbo decoder. The aim of this work is showing a way to bound the channel capacity for single antenna and multiple antennas channels impaired by phase noise generated by instabilities in oscillators driving all the transceivers, and compare the performance of the proposed phase detector to those theoretical limits