4 research outputs found
CFO Estimation for OFDM-based Massive MIMO Systems in Asymptotic Regime
Massive multiple input multiple output (MIMO)
plays a pivotal role in the fifth generation (5G) wireless networks.
However, the carrier frequency offset (CFO) estimation is a challenging issue in the uplink of multi-user massive MIMO systems.
In fact, frequency synchronization can impose a considerable
amount of computational complexity to the base station (BS)
due to a large number of BS antennas. In this paper, thanks
to the properties of massive MIMO in the asymptotic regime,
we develop a simple synchronization technique and derive a
closed form equation for CFO estimation. We show that the phase
information of the covariance matrix of the received signals is
solely dependent on the users’ CFOs. Hence, if a real-valued pilot
is chosen, the CFO values can be straightforwardly calculated
from this matrix. Hence, there is no need to deal with a complex
optimization problem like the other existing CFO estimation
techniques in the literature. Our simulation results testify the
efficacy of our proposed CFO estimation technique. As we have
shown, the performance of our method does not deteriorate as
the number of users increases
Phase-Noise Compensation for OFDM Systems Exploiting Coherence Bandwidth: Modeling, Algorithms, and Analysis
Phase-noise (PN) estimation and compensation are crucial in millimeter-wave
(mmWave) communication systems to achieve high reliability. The PN estimation,
however, suffers from high computational complexity due to its fundamental
characteristics, such as spectral spreading and fast-varying fluctuations. In
this paper, we propose a new framework for low-complexity PN compensation in
orthogonal frequency-division multiplexing systems. The proposed framework also
includes a pilot allocation strategy to minimize its overhead. The key ideas
are to exploit the coherence bandwidth of mmWave systems and to approximate the
actual PN spectrum with its dominant components, resulting in a non-iterative
solution by using linear minimum mean squared-error estimation. The proposed
method obtains a reduction of more than 2.5x in total complexity, as compared
to the existing methods. Furthermore, we derive closed-form expressions for
normalized mean squared-errors (NMSEs) as a function of critical system
parameters, which help in understanding the NMSE behavior in low and high
signal-to-noise ratio regimes. Lastly, we study a trade-off between performance
and pilot-overhead to provide insight into an appropriate approximation of the
PN spectrum.Comment: To appear in IEEE Transactions on Wireless Communication