309 research outputs found
DSP Linearization for Millimeter-Wave All-Digital Receiver Array with Low-Resolution ADCs
Millimeter-wave (mmWave) communications and cell densification are the key
techniques for the future evolution of cellular systems beyond 5G. Although the
current mmWave radio designs are focused on hybrid digital and analog receiver
array architectures, the fully digital architecture is an appealing option due
to its flexibility and support for multi-user multiple-input multiple-output
(MIMO). In order to achieve reasonable power consumption and hardware cost, the
specifications of analog circuits are expected to be compromised, including the
resolution of analog-to-digital converter (ADC) and the linearity of
radio-frequency (RF) front end. Although the state-of-the-art studies focus on
the ADC, the nonlinearity can also lead to severe system performance
degradation when strong input signals introduce inter-modulation distortion
(IMD). The impact of RF nonlinearity becomes more severe with densely deployed
mmWave cells since signal sources closer to the receiver array are more likely
to occur. In this work, we design and analyze the digital IMD compensation
algorithm, and study the relaxation of the required linearity in the RF-chain.
We propose novel algorithms that jointly process digitized samples to recover
amplifier saturation, and relies on beam space operation which reduces the
computational complexity as compared to per-antenna IMD compensation.Comment: 2019 IEEE 20th International Workshop on Signal Processing Advances
in Wireless Communications (SPAWC
Eigenvalue-based Cyclostationary Spectrum Sensing Using Multiple Antennas
In this paper, we propose a signal-selective spectrum sensing method for
cognitive radio networks and specifically targeted for receivers with
multiple-antenna capability. This method is used for detecting the presence or
absence of primary users based on the eigenvalues of the cyclic covariance
matrix of received signals. In particular, the cyclic correlation significance
test is used to detect a specific signal-of-interest by exploiting knowledge of
its cyclic frequencies. The analytical threshold for achieving constant false
alarm rate using this detection method is presented, verified through
simulations, and shown to be independent of both the number of samples used and
the noise variance, effectively eliminating the dependence on accurate noise
estimation. The proposed method is also shown, through numerical simulations,
to outperform existing multiple-antenna cyclostationary-based spectrum sensing
algorithms under a quasi-static Rayleigh fading channel, in both spatially
correlated and uncorrelated noise environments. The algorithm also has
significantly lower computational complexity than these other approaches.Comment: 6 pages, 6 figures, accepted to IEEE GLOBECOM 201
- …