1,023 research outputs found
A Low-Complexity Precoding Scheme for the Downlink of Multi-Cell Multi-User MIMO AF System
Because of its simplicity, amplify-and-forward (AF) is one of the most popular cooperative relaying technique. Relays are used in cooperative communication to improve reliability, coverage or spectral efficiency of cell-edge users. However, relays tend to increase the interferences seen by users of adjacent cells, particularly by the cell-edge users, when used in multi-cell systems. In this paper, we propose a low-complexity precoding scheme to mitigate the effect of other-cell interference (OCI) in cooperative communication. The scheme is designed by taking into account the interference plus noise covariance matrix of each user for mitigating the interference at each receiver by means of precoding at the relay node. Simulation results show the effectiveness of the proposed scheme, both in terms of sum-rate and computational complexity, when compared to other existing OCI-aware precoding algorithms for AF
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
On the Throughput of Large-but-Finite MIMO Networks using Schedulers
This paper studies the sum throughput of the {multi-user}
multiple-input-single-output (MISO) networks in the cases with large but finite
number of transmit antennas and users. Considering continuous and bursty
communication scenarios with different users' data request probabilities, we
derive quasi-closed-form expressions for the maximum achievable throughput of
the networks using optimal schedulers. The results are obtained in various
cases with different levels of interference cancellation. Also, we develop an
efficient scheduling scheme using genetic algorithms (GAs), and evaluate the
effect of different parameters, such as channel/precoding models, number of
antennas/users, scheduling costs and power amplifiers' efficiency, on the
system performance. Finally, we use the recent results on the achievable rates
of finite block-length codes to analyze the system performance in the cases
with short packets. As demonstrated, the proposed GA-based scheduler reaches
(almost) the same throughput as in the exhaustive search-based optimal
scheduler, with substantially less implementation complexity. Moreover, the
power amplifiers' inefficiency and the scheduling delay affect the performance
of the scheduling-based systems significantly
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