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Mohammad Reza Khanzadi

dblp:121/8887 · DBLP profile ↗
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8ranked-venue papers
5as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 7 · 4 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
4 papers
Physical-layer communications · 87% Internet of things and sensor networks · 13%
Theoretical computer science
2 papers
Information theory · 100%

Topics — the 13 heaviest of 13, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information theory
channel capacity
0.422015
On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions · IEEE Trans. Commun. 2015
Capacity of SIMO and MISO Phase-Noise Channels With Common/Separate Oscillators · IEEE Trans. Commun. 2015
Information theory › channel capacity
phase-noise channel
0.422015
On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions · IEEE Trans. Commun. 2015
Capacity of SIMO and MISO Phase-Noise Channels With Common/Separate Oscillators · IEEE Trans. Commun. 2015
Physical-layer communications
MIMO
0.212015
Capacity of SIMO and MISO Phase-Noise Channels With Common/Separate Oscillators · IEEE Trans. Commun. 2015
Information theory › channel capacity
capacity-achieving input distribution
0.212015
On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions · IEEE Trans. Commun. 2015
Internet of things and sensor networks
energy efficiency
0.212014
Bandlimited Power-Efficient Signaling and Pulse Design for Intensity Modulation · IEEE Trans. Commun. 2014
Physical-layer communications › optical communication
intensity modulation
0.212014
Bandlimited Power-Efficient Signaling and Pulse Design for Intensity Modulation · IEEE Trans. Commun. 2014
Physical-layer communications › modulation
pulse shaping
0.212014
Bandlimited Power-Efficient Signaling and Pulse Design for Intensity Modulation · IEEE Trans. Commun. 2014
Physical-layer communications › signal detection
data detection
0.212013
Soft Metrics and Their Performance Analysis for Optimal Data Detection in the Presence of Strong Oscillator Phase Noise · IEEE Trans. Commun. 2013
Physical-layer communications › signal detection
maximum likelihood detection
0.212013
Soft Metrics and Their Performance Analysis for Optimal Data Detection in the Presence of Strong Oscillator Phase Noise · IEEE Trans. Commun. 2013
Physical-layer communications › synchronization
phase noise
0.212013
Soft Metrics and Their Performance Analysis for Optimal Data Detection in the Presence of Strong Oscillator Phase Noise · IEEE Trans. Commun. 2013
Physical-layer communications › channel modeling › gaussian channel
AWGN channel
0.112015
On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions · IEEE Trans. Commun. 2015
Physical-layer communications › RF circuit design
oscillator
0.112015
Capacity of SIMO and MISO Phase-Noise Channels With Common/Separate Oscillators · IEEE Trans. Commun. 2015
Physical-layer communications › error probability analysis
symbol error probability
0.012013
Soft Metrics and Their Performance Analysis for Optimal Data Detection in the Presence of Strong Oscillator Phase Noise · IEEE Trans. Commun. 2013

Methods — techniques the papers use, named apart from their topics

monte carlo simulation · 0.4high-SNR asymptotic analysis · 0.4duality bound · 0.4moment analysis · 0.2gaussian approximation · 0.2
YearPublicationVenuePosition
2015 Receiver Algorithm Based on Differential Signaling for SIMO Phase Noise Channels with Common and Separate Oscillator Configurations
abstract
In this paper, a receiver algorithm consisting of differential transmission and a two-stage detection for a single-input multiple-output (SIMO) phase-noise channels is studied. Specifically, the phases of the QAM modulated data symbols are manipulated before transmission in order to make them more immune to the random rotational effects of phase noise. At the receiver, a two-stage detector is implemented, which first detects the amplitude of the transmitted symbols from a nonlinear combination of the received signal amplitudes. Then in the second stage, the detector performs phase detection. The studied signaling method does not require transmission of any known symbols that act as pilots. Furthermore, no phase noise estimator (or a tracker) is needed at the receiver to compensate the effect of phase noise. This considerably reduces the complexity of the receiver structure. Moreover, it is observed that the studied algorithm can be used for the setups where a common local oscillator or separate independent oscillators drive the radio-frequency circuitries connected to each antenna. Due to the differential encoding/decoding of the phase, weighted averaging can be employed at a multi- antenna receiver, allowing for phase noise suppression to leverage the large number of antennas. Hence, we observe that the performance improves by increasing the number of antennas, especially in the separate oscillator case. Further increasing the number of receive antennas results in a performance error floor, which is a function of the quality of the oscillator at the transmitter.
Mohammad Reza Khanzadi, Rajet Krishnan, Thomas Eriksson
GLOBECOM1
2015 High-SNR capacity of multiple-antenna phase-noise channels with common/separate RF oscillators
abstract
In multiple antenna systems, phase noise due to instabilities of the radio-frequency (RF) oscillators, acts differently depending on whether the RF circuitries connected to each antenna are driven by separate (independent) local oscillators (SLO) or by a common local oscillator (CLO). In this paper, we investigate the high-SNR capacity of single-input multiple-output (SIMO) and multiple-output single-input (MISO) phase-noise channels for both the CLO and the SLO configurations. Our results show that the first-order term in the high-SNR capacity expansion is the same for all scenarios (SIMO/MISO and SLO/CLO), and equal to 0.5 ln(ρ), where ρ stands for the SNR. On the contrary, the second-order term, which we refer to as phase-noise number, turns out to be scenario-dependent. For the SIMO case, the SLO configuration provides a diversity gain, resulting in a larger phase-noise number than for the CLO configuration. For the case of Wiener phase noise, a diversity gain of at least 0.5 ln(M) can be achieved, where M is the number of receive antennas. For the MISO, the CLO configuration yields a higher phase-noise number than the SLO configuration. This is because with the CLO configuration one can obtain a coherent-combining gain through maximum ratio transmission (a.k.a. conjugate beamforming). This gain is unattainable with the SLO configuration.
Mohammad Reza Khanzadi, Giuseppe Durisi, Thomas Eriksson
ICC1
2015 Capacity of SIMO and MISO Phase-Noise Channels With Common/Separate Oscillators
abstract
In multiple antenna systems, phase noise due to instabilities of the radio-frequency (RF) oscillators, acts differently depending on whether the RF circuitries connected to each antenna are driven by separate (independent) local oscillators (SLO) or by a common local oscillator (CLO). In this paper, we investigate the high-SNR capacity of single-input multiple-output (SIMO) and multiple-output single-input (MISO) phase-noise channels for both the CLO and the SLO configurations. Our results show that the first-order term in the high-SNR capacity expansion is the same for all scenarios (SIMO/MISO and SLO/CLO), and equal to 0.5 ln(p), where p stands for the SNR. On the contrary, the second-order term, which we refer to as phase-noise number, turns out to be scenario-dependent. For the SIMO case, the SLO configuration provides a diversity gain, resulting in a larger phase-noise number than for the CLO configuration. For the case of Wiener phase noise, a diversity gain of at least 0.5 ln(M) can be achieved, where M is the number of receive antennas. For the MISO, the CLO configuration yields a higher phase-noise number than the SLO configuration. This is because with the CLO configuration one can obtain a coherent-combining gain through maximum ratio transmission (a.k.a. conjugate beamforming). This gain is unattainable with the SLO configuration.
Mohammad Reza Khanzadi, Giuseppe Durisi, Thomas Eriksson
IEEE Trans. Commun.1
2015 On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions
abstract
In this paper, the capacity of the additive white Gaussian noise (AWGN) channel, affected by time-varying Wiener phase noise is investigated. Tight upper and lower bounds on the capacity of this channel are developed. The upper bound is obtained by using the duality approach, and by considering a specific distribution over the output of the channel. In order to lower-bound the capacity, first a family of capacity-achieving input distributions is found by solving a functional optimization of the channel mutual information. Then, lower bounds on the capacity are obtained by drawing samples from the proposed distributions through Monte Carlo simulations. The proposed capacity-achieving input distributions are circularly symmetric, non-Gaussian, and the input amplitudes are correlated over time. The evaluated capacity bounds are tight for a wide range of signal-to-noise-ratio (SNR) values, and thus they can be used to quantify the capacity. Specifically, the bounds follow the well-known AWGN capacity curve at low SNR, while at high SNR, they coincide with the high-SNR capacity result available in the literature for the phase-noise channel.
Mohammad Reza Khanzadi, Rajet Krishnan, Johan Söder, Thomas Eriksson
IEEE Trans. Commun.1
2014 Bandlimited Power-Efficient Signaling and Pulse Design for Intensity Modulation
abstract
In this paper, a new method for power-efficient intersymbol interference-free transmission over the bandlimited intensity-modulation direct-detection channel is proposed. A new time-varying bias signal is added to the transmitted signal to make it nonnegative and provide a more power-efficient transmission than the previously considered constant bias. To exploit the benefits of the new signaling method, Nyquist and root-Nyquist pulses suitable for the use with this kind of bias are designed using two different methods. In the first method, new pulses are obtained by adding Nyquist pulses in the time domain with different combining coefficients, whereas in the second method, the pulses are obtained by the design of their frequency response. Analytical expressions for the asymptotic optical power efficiency and symbol error rate of the proposed schemes are derived and evaluated. At a spectral efficiency of 1 b/s/Hz, using on-off keying modulation and the proposed bias signal and pulses, up to 0.628 dB gains in asymptotic power efficiency can be achieved compared to the previously best known signaling scheme, which is based on squared sinc pulse shaping.
Cristian B. Czegledi, Mohammad Reza Khanzadi, Erik Agrell
IEEE Trans. Commun.2
2013 Effect of synchronizing coordinated base stations on phase noise estimation
abstract
In this paper, we study the problem of oscillator phase noise (PN) estimation in coordinated multi-point (CoMP) transmission systems. Specifically, we investigate the effect of phase synchronization between coordinated base stations (BSs) on PN estimation at the user receiver. In this respect, the Bayesian Cramér-Rao bound for PN estimation is derived which is a function of the level of phase synchronization between the coordinated BSs. Results show that quality of BS synchronization has a significant effect on the PN estimation.
Mohammad Reza Khanzadi, Rajet Krishnan, Thomas Eriksson
ICASSP1
2013 Soft Metrics and Their Performance Analysis for Optimal Data Detection in the Presence of Strong Oscillator Phase Noise
abstract
In this paper, we address the classical problem of maximum-likelihood (ML) detection of data in the presence of random phase noise. We consider a system, where the random phase noise affecting the received signal is first compensated by a tracker/estimator. Then the phase error and its statistics are used for deriving the ML detector. Specifically, we derive an ML detector based on a Gaussian assumption for the phase error probability density function (PDF). Further without making any assumptions on the phase error PDF, we show that the actual ML detector can be reformulated as a weighted sum of central moments of the phase error PDF. We present a simple approximation of this new ML rule assuming that the phase error distribution is unknown. The ML detectors derived are also the aposteriori probabilities of the transmitted symbols, and are referred to as soft metrics. Then, using the detector developed based on Gaussian phase error assumption, we derive the symbol error probability (SEP) performance and error floor analytically for arbitrary constellations. Finally we compare SEP performance of the various detectors/metrics in this work and those from literature for different signal constellations, phase noise scenarios and SNR values.
Rajet Krishnan, Mohammad Reza Khanzadi, Thomas Eriksson, Tommy Svensson
IEEE Trans. Commun.2
2012 Variational Bayesian framework for receiver design in the presence of phase noise in MIMO systems
abstract
In this work, the problem of receiver design for phase noise estimation and data detection in the presence of oscillator phase noise in a point-to-point multiple-input multiple-output (MIMO) system is addressed. First, we discuss some interesting and challenging aspects in receiver design for MIMO systems in the presence of Wiener phase noise. Then, using the variational Bayesian (VB) framework, a joint iterative phase noise estimator and symbol detector are developed based on inverse Gibbs or variational free energy maximization. Further, the symbol error probability (SEP) of the newly proposed iterative scheme is compared with the optimal maximum likelihood (ML) detector with perfect phase information for 16-phase shift keying (PSK) and 16-quadrature amplitude modulation (QAM) schemes.
Rajet Krishnan, Mohammad Reza Khanzadi, Lennart Svensson, Thomas Eriksson, Tommy Svensson
WCNC2