148 research outputs found
Generalised MBER-based vector precoding design for multiuser transmission
We propose a generalized vector precoding (VP) design based on the minimum bit error rate (MBER) criterion for multiuser transmission in the downlink of a multiuser system, where the base station (BS) equipped with multiple transmitting antennas communicates with single-receiving-antenna mobile station (MS) receivers each having a modulo device. Given the knowledge of the channel state information and the current information symbol vector to be transmitted, our scheme directly generates the effective symbol vector based on the MBER criterion using the particle swarm optimization (PSO) algorithm. The proposed PSO-aided generalized MBER VP scheme is shown to outperform the powerful minimum mean-square-error (MMSE) VP and improved MMSE-VP benchmarks, particularly for rank-deficient systems, where the number of BS transmitting antennas is lower than the number of MSs supported
Sum Rate and Fairness Analysis for the MU-MIMO Downlink under PSK Signalling: Interference Suppression vs Exploitation
In this paper, we analyze the sum rate performance of multi-user
multiple-input multiple-output (MU-MIMO) systems, with a finite constellation
phase-shift keying (PSK) input alphabet. We analytically calculate and compare
the achievable sum rate in three downlink transmission scenarios: 1) without
precoding, 2) with zero forcing (ZF) precoding 3) with closed form constructive
interference (CI) precoding technique. In light of this, new analytical
expressions for the average sum rate are derived in the three cases, and Monte
Carlo simulations are provided throughout to validate the analysis.
Furthermore, based on the derived expressions, a power allocation scheme that
can ensure fairness among the users is also proposed. The results in this work
demonstrate that, the CI strictly outperforms the other two schemes, and the
performance gap between the considered schemes increases with increase in the
MIMO size. In addition, the CI provides higher fairness and the power
allocation algorithm proposed in this paper can achieve maximum fairness index
Scaling up MIMO: Opportunities and Challenges with Very Large Arrays
This paper surveys recent advances in the area of very large MIMO systems.
With very large MIMO, we think of systems that use antenna arrays with an
order of magnitude more elements than in systems being built today, say a
hundred antennas or more. Very large MIMO entails an unprecedented number of
antennas simultaneously serving a much smaller number of terminals. The
disparity in number emerges as a desirable operating condition and a practical
one as well. The number of terminals that can be simultaneously served is
limited, not by the number of antennas, but rather by our inability to acquire
channel-state information for an unlimited number of terminals. Larger numbers
of terminals can always be accommodated by combining very large MIMO technology
with conventional time- and frequency-division multiplexing via OFDM. Very
large MIMO arrays is a new research field both in communication theory,
propagation, and electronics and represents a paradigm shift in the way of
thinking both with regards to theory, systems and implementation. The ultimate
vision of very large MIMO systems is that the antenna array would consist of
small active antenna units, plugged into an (optical) fieldbus.Comment: Accepted for publication in the IEEE Signal Processing Magazine,
October 201
Vector perturbation technique
La “vector perturbation technique” è una tecnica di codifica che permette di avvicinarsi alla capacità teorica del canale in un sistema MIMO. Questa tecnica va a operare sul vettore dati da trasmettere e si articola in quattro punti fondamentali: Channel Inversion, Regolarizzazione, Perturbazione e Perturbazione Regolarizzata. Grazie ad essa è possibile ottenere una capacità che cresce linearmente con il numero minimo tra le antenne trasmittenti/riceventi del sistem
Interference-Aware RZF Precoding for Multi Cell Downlink Systems
Recently, a structure of an optimal linear precoder for multi cell downlink
systems has been described in [1, Eq (3.33)]. Other references (e.g., [2,3])
have used simplified versions of the precoder to obtain promising performance
gains. These gains have been hypothesized to stem from the additional degrees
of freedom that allow for interference mitigation through interference
relegation to orthogonal subspaces. However, no conclusive or rigorous
understanding has yet been developed. In this paper, we build on an intuitive
interference induction trade-off and the aforementioned precoding structure to
propose an interference aware RZF (iaRZF) precoding scheme for multi cell
downlink systems and we analyze its rate performance. Special emphasis is
placed on the induced interference mitigation mechanism of iaRZF. For example,
we will verify the intuitive expectation that the precoder structure can either
completely remove induced inter-cell or intra-cell interference. We state new
results from large-scale random matrix theory that make it possible to give
more intuitive and insightful explanations of the precoder behavior, also for
cases involving imperfect channel state information (CSI). We remark especially
that the interference-aware precoder makes use of all available information
about interfering channels to improve performance. Even very poor CSI allows
for significant sum-rate gains. Our obtained insights are then used to propose
heuristic precoder parameters for arbitrary systems, whose effectiveness are
shown in more involved system scenarios. Furthermore, calculation and
implementation of these parameters does not require explicit inter base station
cooperation.Comment: Accepted for publication in IEEE Transactions on Signal Processing,
201
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