78 research outputs found
Modeling and Efficient Cancellation of Nonlinear Self-Interference in MIMO Full-Duplex Transceivers
This paper addresses the modeling and digital cancellation of
self-interference in in-band full-duplex (FD) transceivers with multiple
transmit and receive antennas. The self-interference modeling and the proposed
nonlinear spatio-temporal digital canceller structure takes into account, by
design, the effects of I/Q modulator imbalances and power amplifier (PA)
nonlinearities with memory, in addition to the multipath self-interference
propagation channels and the analog RF cancellation stage. The proposed
solution is the first cancellation technique in the literature which can handle
such a self-interference scenario. It is shown by comprehensive simulations
with realistic RF component parameters and with two different PA models to
clearly outperform the current state-of-the-art digital self-interference
cancellers, and to clearly extend the usable transmit power range.Comment: 7 pages, 5 figures. To be presented in the 2014 International
Workshop on Emerging Technologies for 5G Wireless Cellular Network
Digital Pre-distortion for Interference Reduction in Dynamic Spectrum Access Networks
Given the ever increasing reliance of today’s society on ubiquitous wireless access, the paradigm of dynamic spectrum access (DSA) as been proposed and implemented for utilizing the limited wireless spectrum more efficiently. Orthogonal frequency division multiplexing (OFDM) is growing in popularity for adoption into wireless services employing DSA frame- work, due to its high bandwidth efficiency and resiliency to multipath fading. While these advantages have been proven for many wireless applications, including LTE-Advanced and numerous IEEE wireless standards, one potential drawback of OFDM or its non-contiguous variant, NC-OFDM, is that it exhibits high peak-to-average power ratios (PAPR), which can induce in-band and out-of-band (OOB) distortions when the peaks of the waveform enter the compression region of the transmitter power amplifier (PA). Such OOB emissions can interfere with existing neighboring transmissions, and thereby severely deteriorate the reliability of the DSA network. A performance-enhancing digital pre-distortion (DPD) technique compensating for PA and in-phase/quadrature (I/Q) modulator distortions is proposed in this dissertation. Al- though substantial research efforts into designing DPD schemes have already been presented in the open literature, there still exists numerous opportunities to further improve upon the performance of OOB suppression for NC-OFDM transmission in the presence of RF front-end impairments. A set of orthogonal polynomial basis functions is proposed in this dissertation together with a simplified joint DPD structure. A performance analysis is presented to show that the OOB emissions is reduced to approximately 50 dBc with proposed algorithms employed during NC-OFDM transmission. Furthermore, a novel and intuitive DPD solution that can minimize the power regrowth at any pre-specified frequency in the spurious domain is proposed in this dissertation. Conventional DPD methods have been proven to be able to effectively reduce the OOB emissions that fall on top of adjacent channels. However more spectral emissions in more distant frequency ranges are generated by employing such DPD solutions, which are potentially in violation of the spurious emission limit. At the same time, the emissions in adjacent channel must be kept under the OOB limit. To the best of the author’s knowledge, there has not been extensive research conducted on this topic. Mathematical derivation procedures of the proposed algorithm are provided for both memoryless nonlinear model and memory-based nonlinear model. Simulation results show that the proposed method is able to provide a good balance of OOB emissions and emissions in the far out spurious domain, by reducing the spurious emissions by 4-5 dB while maintaining the adjacent channel leakage ratio (ACLR) improvement by at least 10 dB, comparing to the PA output spectrum without any DPD
On the Implementation Complexity of Digital Full-Duplex Self-Interference Cancellation
In-band full-duplex systems promise to further increase the throughput of
wireless systems, by simultaneously transmitting and receiving on the same
frequency band. However, concurrent transmission generates a strong
self-interference signal at the receiver, which requires the use of
cancellation techniques. A wide range of techniques for analog and digital
self-interference cancellation have already been presented in the literature.
However, their evaluation focuses on cases where the underlying physical
parameters of the full-duplex system do not vary significantly. In this paper,
we focus on adaptive digital cancellation, motivated by the fact that physical
systems change over time. We examine some of the different cancellation methods
in terms of their performance and implementation complexity, considering the
cost of both cancellation and training. We then present a comparative analysis
of all these methods to determine which perform better under different system
performance requirements. We demonstrate that with a neural network approach,
the reduction in arithmetic complexity for the same cancellation performance
relative to a state-of-the-art polynomial model is several orders of magnitude.Comment: Presented at the 2020 Asilomar Conference for Signals, Systems, and
Computer
Adaptive Nonlinear RF Cancellation for Improved Isolation in Simultaneous Transmit-Receive Systems
This paper proposes an active radio frequency (RF) cancellation solution to
suppress the transmitter (TX) passband leakage signal in radio transceivers
supporting simultaneous transmission and reception. The proposed technique is
based on creating an opposite-phase baseband equivalent replica of the TX
leakage signal in the transceiver digital front-end through adaptive nonlinear
filtering of the known transmit data, to facilitate highly accurate
cancellation under a nonlinear TX power amplifier (PA). The active RF
cancellation is then accomplished by employing an auxiliary transmitter chain,
to generate the actual RF cancellation signal, and combining it with the
received signal at the receiver (RX) low noise amplifier (LNA) input. A
closed-loop parameter learning approach, based on the decorrelation principle,
is also developed to efficiently estimate the coefficients of the nonlinear
cancellation filter in the presence of a nonlinear TX PA with memory, finite
passive isolation, and a nonlinear RX LNA. The performance of the proposed
cancellation technique is evaluated through comprehensive RF measurements
adopting commercial LTE-Advanced transceiver hardware components. The results
show that the proposed technique can provide an additional suppression of up to
54 dB for the TX passband leakage signal at the RX LNA input, even at
considerably high transmit power levels and with wide transmission bandwidths.
Such novel cancellation solution can therefore substantially improve the TX-RX
isolation, hence reducing the requirements on passive isolation and RF
component linearity, as well as increasing the efficiency and flexibility of
the RF spectrum use in the emerging 5G radio networks.Comment: accepted to IEE
Modeling and Linearization of MIMO RF Transmitters
Multiple-input multiple-output (MIMO) technology will continue to play a vital
role in next-generation wireless systems, e.g., the fifth-generation wireless networks
(5G). Large-scale antenna arrays (also called massive MIMO) seem to be the most
promising physical layer solution for meeting the ever-growing demand for high
spectral efficiency. Large-scale MIMO arrays are typically deployed with high
integration and using low-cost components. Hence, they are prone to different
hardware impairments such as crosstalk between the transmit antennas and power
amplifier (PA) nonlinearities, which distort the transmitted signal. To avert the
performance degradation due to these impairments, it is essential to have mechanisms
for predicting the output of the MIMO arrays. Such prediction mechanisms are
mandatory for performance evaluation and, more importantly, for the adoption of
proper compensation techniques such as digital predistortion (DPD) schemes. This
has stirred a considerable amount of interest among researchers to develop new
hardware and signal processing solutions to address the requirements of large-scale
MIMO systems.
In the context of MIMO systems, one particular problem is that the hardware
cost and complexity scale up with the increase of the size of the MIMO system.
As a result, the MIMO systems tend to be implemented on a chip and are very
compact. Reduction of the cost by reducing the bill of material is possible when
several components are eliminated. The reuse of already existing hardware is an
alternative solution. As a result, such systems are prone to excessive sources of
distortion, such as crosstalk. Accordingly, crosstalk in MIMO systems in its simplest
form can affect the DPD coefficient estimation scheme. In this thesis, the effect of
crosstalk on two main DPD estimation techniques, know as direct learning algorithm
(DLA) and indirect learning algorithm (ILA), is studied.
The PA behavioral modeling and DPD scheme face several challenges that seek
cost-efficient and flexible solutions too. These techniques require constant capture
of the PA output feedback signal, which ultimately requires the implementation
of a complete transmitter observation receiver (TOR) chain for the individual
transmit path. In this thesis, a technique to reuse the receiver path of the MIMO
TDD transceiver as a TOR is developed, which is based on over-the-air (OTA)
measurements. With these techniques, individual PA behavioral modeling and DPD
can be done by utilizing a few receivers of the MIMO TDD system. To use OTA
measurements, an on-site antenna calibration scheme is developed to individually
estimate the coupling between the transmitter and the receiver antennas.
Furthermore, a digital predistortion technique for compensating the nonlinearity
of several PAs in phased arrays is presented. The phased array can be a subset of
massive MIMO systems, and it uses several antennas to steer the transmitted signal
in a particular direction by appropriately assigning the magnitude and the phase
of the transmitted signal from each antenna. The particular structure of phased
arrays requires the linearization of several PAs with a single DPD. By increasing the
number of RF branches and consequently increasing the number of PAs in the phased
array, the linearization task becomes challenging. The DPD must be optimized to
results in the best overall linear performance of the phased array in the field. The
problem of optimized DPD for phased array has not been addressed appropriately in
the literature.
In this thesis, a DPD technique is developed based on an optimization problem
to address the linearization of PAs with high variations. The technique continuously
optimizes the DPD coefficients through several iterations considering the effect of
each PA simultaneously. Therefore, it results in the best optimized DPD performance
for several PAs.
Extensive analysis, simulations, and measurement evaluation is carried out as
a proof of concept. The different proposed techniques are compared with conventional approaches, and the results are presented. The techniques proposed in this
thesis enable cost-efficient and flexible signal processing approaches to facilitate the
development of future wireless communication systems
Hardware Implementation of Neural Self-Interference Cancellation
In-band full-duplex systems can transmit and receive information
simultaneously on the same frequency band. However, due to the strong
self-interference caused by the transmitter to its own receiver, the use of
non-linear digital self-interference cancellation is essential. In this work,
we describe a hardware architecture for a neural network-based non-linear
self-interference (SI) canceller and we compare it with our own hardware
implementation of a conventional polynomial based SI canceller. In particular,
we present implementation results for a shallow and a deep neural network SI
canceller as well as for a polynomial SI canceller. Our results show that the
deep neural network canceller achieves a hardware efficiency of up to
Msamples/s/mm and an energy efficiency of up to nJ/sample, which is
and better than the polynomial SI canceller,
respectively. These results show that NN-based methods applied to
communications are not only useful from a performance perspective, but can also
be a very effective means to reduce the implementation complexity.Comment: Accepted for publication in IEEE Journal on Emerging and Selected
Topics in Circuits and System
Performance Analysis of Coherent and Noncoherent Modulation under I/Q Imbalance
In-phase/quadrature-phase Imbalance (IQI) is considered a major
performance-limiting impairment in direct-conversion transceivers. Its effects
become even more pronounced at higher carrier frequencies such as the
millimeter-wave frequency bands being considered for 5G systems. In this paper,
we quantify the effects of IQI on the performance of different modulation
schemes under multipath fading channels. This is realized by developing a
general framework for the symbol error rate (SER) analysis of coherent phase
shift keying, noncoherent differential phase shift keying and noncoherent
frequency shift keying under IQI effects. In this context, the moment
generating function of the signal-to-interference-plus-noise-ratio is first
derived for both single-carrier and multi-carrier systems suffering from
transmitter (TX) IQI only, receiver (RX) IQI only and joint TX/RX IQI.
Capitalizing on this, we derive analytic expressions for the SER of the
different modulation schemes. These expressions are corroborated by comparisons
with corresponding results from computer simulations and they provide insights
into the dependence of IQI on the system parameters. We demonstrate that the
effects of IQI differ considerably depending on the considered system as some
cases of single-carrier transmission appear robust to IQI, whereas
multi-carrier systems experiencing IQI at the RX require compensation in order
to achieve a reliable communication link
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