79 research outputs found
Linear Precoding Based on Polynomial Expansion: Large-Scale Multi-Cell MIMO Systems
Large-scale MIMO systems can yield a substantial improvement in spectral
efficiency for future communication systems. Due to the finer spatial
resolution achieved by a huge number of antennas at the base stations, these
systems have shown to be robust to inter-user interference and the use of
linear precoding is asymptotically optimal. However, most precoding schemes
exhibit high computational complexity as the system dimensions increase. For
example, the near-optimal RZF requires the inversion of a large matrix. This
motivated our companion paper, where we proposed to solve the issue in
single-cell multi-user systems by approximating the matrix inverse by a
truncated polynomial expansion (TPE), where the polynomial coefficients are
optimized to maximize the system performance. We have shown that the proposed
TPE precoding with a small number of coefficients reaches almost the
performance of RZF but never exceeds it. In a realistic multi-cell scenario
involving large-scale multi-user MIMO systems, the optimization of RZF
precoding has thus far not been feasible. This is mainly attributed to the high
complexity of the scenario and the non-linear impact of the necessary
regularizing parameters. On the other hand, the scalar weights in TPE precoding
give hope for possible throughput optimization. Following the same methodology
as in the companion paper, we exploit random matrix theory to derive a
deterministic expression for the asymptotic SINR for each user. We also provide
an optimization algorithm to approximate the weights that maximize the
network-wide weighted max-min fairness. The optimization weights can be used to
mimic the user throughput distribution of RZF precoding. Using simulations, we
compare the network throughput of the TPE precoding with that of the suboptimal
RZF scheme and show that our scheme can achieve higher throughput using a TPE
order of only 3
Interference Exploitation-based Hybrid Precoding with Robustness Against Phase Errors
Hybrid analog-digital precoding significantly reduces the hardware costs in
massive MIMO transceivers when compared to fully-digital precoding at the
expense of increased transmit power. In order to mitigate the above shortfall,
we use the concept of constructive interference-based precoding, which has been
shown to offer significant transmit power savings when compared with the
conventional interference suppression-based precoding in fully-digital
multiuser MIMO systems. Moreover, in order to circumvent the potential
quality-of-service degradation at the users due to the hardware impairments in
the transmitters, we judiciously incorporate robustness against such
vulnerabilities in the precoder design. Since the undertaken constructive
interference-based robust hybrid precoding problem is nonconvex with infinite
constraints and thus difficult to solve optimally, we decompose the problem
into two subtasks, namely, analog precoding and digital precoding. In this
paper, we propose an algorithm to compute the optimal constructive
interference-based robust digital precoders. Furthermore, we devise a scheme to
facilitate the implementation of the proposed algorithm in a low-complexity and
distributed manner. We also discuss block-level analog precoding techniques.
Simulation results demonstrate the superiority of the proposed algorithm and
its implementation scheme over the state-of-the-art methods
Linear Precoding with Low-Resolution DACs for Massive MU-MIMO-OFDM Downlink
We consider the downlink of a massive multiuser (MU) multiple-input
multiple-output (MIMO) system in which the base station (BS) is equipped with
low-resolution digital-to-analog converters (DACs). In contrast to most
existing results, we assume that the system operates over a frequency-selective
wideband channel and uses orthogonal frequency division multiplexing (OFDM) to
simplify equalization at the user equipments (UEs). Furthermore, we consider
the practically relevant case of oversampling DACs. We theoretically analyze
the uncoded bit error rate (BER) performance with linear precoders (e.g., zero
forcing) and quadrature phase-shift keying using Bussgang's theorem. We also
develop a lower bound on the information-theoretic sum-rate throughput
achievable with Gaussian inputs, which can be evaluated in closed form for the
case of 1-bit DACs. For the case of multi-bit DACs, we derive approximate, yet
accurate, expressions for the distortion caused by low-precision DACs, which
can be used to establish lower bounds on the corresponding sum-rate throughput.
Our results demonstrate that, for a massive MU-MIMO-OFDM system with a
128-antenna BS serving 16 UEs, only 3--4 DAC bits are required to achieve an
uncoded BER of 10^-4 with a negligible performance loss compared to the
infinite-resolution case at the cost of additional out-of-band emissions.
Furthermore, our results highlight the importance of taking into account the
inherent spatial and temporal correlations caused by low-precision DACs
A Versatile Low-Complexity Feedback Scheme for FDD Systems via Generative Modeling
We propose a versatile feedback scheme for both single- and multi-user
multiple-input multiple-output (MIMO) frequency division duplex (FDD) systems.
Particularly, we propose utilizing a Gaussian mixture model (GMM) with a
reduced number of parameters for codebook construction, feedback encoding, and
precoder design. The GMM is fitted offline at the base station (BS) to uplink
training samples to approximate the channel distribution of all possible mobile
terminals (MTs) within the BS cell. Subsequently, a codebook is constructed,
with each element based on one GMM component. Extracting directional
information from the codebook or exploiting the GMM's sample generation ability
facilitates joint precoder design for a multi-user MIMO system using
state-of-the-art precoding algorithms. After offloading the GMM to the MTs,
they can easily determine their feedback by selecting the index of the GMM
component with the highest responsibility for their received pilot signal. This
strategy exhibits low complexity and supports parallelization. Simulations
demonstrate that the proposed approach outperforms conventional methods, which
either estimate the channel and utilize a Lloyd codebook or use a deep neural
network to determine the feedback in terms of spectral efficiency or sum-rate.
The performance gains can be exploited to deploy systems with fewer pilots or
feedback bits.Comment: Copyright IEEE. Personal use is permitted, but
republication/redistribution requires IEEE permission. See
https://www.ieee.org/publications/rights/index.html for more informatio
- …