15,293 research outputs found
A Two-stage approach to harmonic rejection mixing using blind interference cancelling
Current analog harmonic rejection mixers typically provide 30–40 dB of harmonic rejection, which is often not sufficient. We present a mixed analog-digital approach to harmonic rejection mixing that uses a digital interference canceler to reject the strongest interferer. Simulations indicate that, given a practical RF scenario, the digital canceler is able to improve the signal-to-interference ratio by 30–45 dB
A Digital Predistortion Scheme Exploiting Degrees-of-Freedom for Massive MIMO Systems
The primary source of nonlinear distortion in wireless transmitters is the
power amplifier (PA). Conventional digital predistortion (DPD) schemes use
high-order polynomials to accurately approximate and compensate for the
nonlinearity of the PA. This is not practical for scaling to tens or hundreds
of PAs in massive multiple-input multiple-output (MIMO) systems. There is more
than one candidate precoding matrix in a massive MIMO system because of the
excess degrees-of-freedom (DoFs), and each precoding matrix requires a
different DPD polynomial order to compensate for the PA nonlinearity. This
paper proposes a low-order DPD method achieved by exploiting massive DoFs of
next-generation front ends. We propose a novel indirect learning structure
which adapts the channel and PA distortion iteratively by cascading adaptive
zero forcing precoding and DPD. Our solution uses a 3rd order polynomial to
achieve the same performance as the conventional DPD using an 11th order
polynomial for a 100x10 massive MIMO configuration. Experimental results show a
70% reduction in computational complexity, enabling ultra-low latency
communications.Comment: IEEE International Conference on Communications 201
Principles of Neuromorphic Photonics
In an age overrun with information, the ability to process reams of data has
become crucial. The demand for data will continue to grow as smart gadgets
multiply and become increasingly integrated into our daily lives.
Next-generation industries in artificial intelligence services and
high-performance computing are so far supported by microelectronic platforms.
These data-intensive enterprises rely on continual improvements in hardware.
Their prospects are running up against a stark reality: conventional
one-size-fits-all solutions offered by digital electronics can no longer
satisfy this need, as Moore's law (exponential hardware scaling),
interconnection density, and the von Neumann architecture reach their limits.
With its superior speed and reconfigurability, analog photonics can provide
some relief to these problems; however, complex applications of analog
photonics have remained largely unexplored due to the absence of a robust
photonic integration industry. Recently, the landscape for
commercially-manufacturable photonic chips has been changing rapidly and now
promises to achieve economies of scale previously enjoyed solely by
microelectronics.
The scientific community has set out to build bridges between the domains of
photonic device physics and neural networks, giving rise to the field of
\emph{neuromorphic photonics}. This article reviews the recent progress in
integrated neuromorphic photonics. We provide an overview of neuromorphic
computing, discuss the associated technology (microelectronic and photonic)
platforms and compare their metric performance. We discuss photonic neural
network approaches and challenges for integrated neuromorphic photonic
processors while providing an in-depth description of photonic neurons and a
candidate interconnection architecture. We conclude with a future outlook of
neuro-inspired photonic processing.Comment: 28 pages, 19 figure
Survey of Inter-satellite Communication for Small Satellite Systems: Physical Layer to Network Layer View
Small satellite systems enable whole new class of missions for navigation,
communications, remote sensing and scientific research for both civilian and
military purposes. As individual spacecraft are limited by the size, mass and
power constraints, mass-produced small satellites in large constellations or
clusters could be useful in many science missions such as gravity mapping,
tracking of forest fires, finding water resources, etc. Constellation of
satellites provide improved spatial and temporal resolution of the target.
Small satellite constellations contribute innovative applications by replacing
a single asset with several very capable spacecraft which opens the door to new
applications. With increasing levels of autonomy, there will be a need for
remote communication networks to enable communication between spacecraft. These
space based networks will need to configure and maintain dynamic routes, manage
intermediate nodes, and reconfigure themselves to achieve mission objectives.
Hence, inter-satellite communication is a key aspect when satellites fly in
formation. In this paper, we present the various researches being conducted in
the small satellite community for implementing inter-satellite communications
based on the Open System Interconnection (OSI) model. This paper also reviews
the various design parameters applicable to the first three layers of the OSI
model, i.e., physical, data link and network layer. Based on the survey, we
also present a comprehensive list of design parameters useful for achieving
inter-satellite communications for multiple small satellite missions. Specific
topics include proposed solutions for some of the challenges faced by small
satellite systems, enabling operations using a network of small satellites, and
some examples of small satellite missions involving formation flying aspects.Comment: 51 pages, 21 Figures, 11 Tables, accepted in IEEE Communications
Surveys and Tutorial
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
Simultaneous Transmission and Reception: Algorithm, Design and System Level Performance
Full Duplex or Simultaneous transmission and reception (STR) in the same
frequency at the same time can potentially double the physical layer capacity.
However, high power transmit signal will appear at receive chain as echoes with
powers much higher than the desired received signal. Therefore, in order to
achieve the potential gain, it is imperative to cancel these echoes. As these
high power echoes can saturate low noise amplifier (LNA) and also digital
domain echo cancellation requires unrealistically high resolution
analog-to-digital converter (ADC), the echoes should be cancelled or suppressed
sufficiently before LNA. In this paper we present a closed-loop echo
cancellation technique which can be implemented purely in analogue domain. The
advantages of our method are multiple-fold: it is robust to phase noise, does
not require additional set of antennas, can be applied to wideband signals and
the performance is irrelevant to radio frequency (RF) impairments in transmit
chain. Next, we study a few protocols for STR systems in carrier sense multiple
access (CSMA) network and investigate MAC level throughput with realistic
assumptions in both single cell and multiple cells. We show that STR can reduce
hidden node problem in CSMA network and produce gains of up to 279% in maximum
throughput in such networks. Finally, we investigate the application of STR in
cellular systems and study two new unique interferences introduced to the
system due to STR, namely BS-BS interference and UE-UE interference. We show
that these two new interferences will hugely degrade system performance if not
treated appropriately. We propose novel methods to reduce both interferences
and investigate the performances in system level.Comment: 20 pages. This manuscript will appear in the IEEE Transactions on
Wireless Communication
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