152 research outputs found
To Promote the Sustainable Development of Regional Economies in South Asia by Enhancing Economic Cooperation of the Pan-Red River Basin
In the significant trend of economic globalization, the regional competence becomes increasingly fierce. China and Southeast Asia are inevitably involved in this competition. In framework of China-ASEAN Free Trade Area, the Pan-Red River basin is the complement and expansion of it. The Red River mainly flows through China, Vietnam and Laos, especially China and Vietnam. The concept of the Pan-Red River basin plays an important role under the new situation. The overall stable political and economical situation, the complement of industrial resources, the improvement of transportation conditions and the further development of regional cooperation all provide certain foundations and conditions for accelerating the development of the Pan-Red River basin. In order to achieve the development of the Pan-Red River basin, developing consensus should be reached, regional factors flow and industrial upgrading and transfer should be achieved, transportation advantage should be played, the logistics centers of China and Vietnam should be built, multipolar regional development impetus should be achieved, and the port construction and border regional cooperation zone should also be built and strengthened
Intelligent Reflecting Surface Assisted Massive MIMO Communications
In a practical massive MIMO (multiple-input multiple-output) system, the
number of antennas at a base station (BS) is constrained by the space and cost
factors, which limits the throughput gain promised by theoretical analysis.
This paper thus studies the feasibility of adopting the intelligent reflecting
surface (IRS) to further improve the beamforming gain of the uplink
communications in a massive MIMO system. Under such a novel system, the central
question lies in whether the IRS is able to enhance the network throughput as
expected, if the channel estimation overhead is taken into account. In this
paper, we first show that the favorable propagation property for the
conventional massive MIMO system without IRS, i.e., the channels of arbitrary
two users are orthogonal, no longer holds for the IRS-assisted massive MIMO
system, due to its special channel property that each IRS element reflects the
signals from all the users to the BS via the same channel. As a result, the
maximal-ratio combining (MRC) receive beamforming strategy leads to strong
inter-user interference and thus even lower user rates than those of the
massive MIMO system without IRS. To tackle this challenge, we propose a novel
strategy for zero-forcing (ZF) beamforming design at the BS and reflection
coefficients design at the IRS to efficiently null the inter-user interference.
Under our proposed strategy, it is rigorously shown that even if the channel
estimation overhead is considered, the IRS-assisted massive MIMO system can
always achieve higher throughput compared to its counterpart without IRS,
despite the fact that the favorable propagation property no longer holds.Comment: Invited paper, accepted by IEEE SPAWC 202
Semantic Communication-Empowered Physical-layer Network Coding
In a two-way relay channel (TWRC), physical-layer network coding (PNC)
doubles the system throughput by turning superimposed signals transmitted
simultaneously by different end nodes into useful network-coded information
(known as PNC decoding). Prior works indicated that the PNC decoding
performance is affected by the relative phase offset between the received
signals from different nodes. In particular, some "bad" relative phase offsets
could lead to huge performance degradation. Previous solutions to mitigate the
relative phase offset effect were limited to the conventional bit-oriented
communication paradigm, aiming at delivering a given information stream as
quickly and reliably as possible. In contrast, this paper puts forth the first
semantic communication-empowered PNC-enabled TWRC to address the relative phase
offset issue, referred to as SC-PNC. Despite the bad relative phase offsets,
SC-PNC directly extracts the semantic meaning of transmitted messages rather
than ensuring accurate bit stream transmission. We jointly design deep neural
network (DNN)-based transceivers at the end nodes and propose a semantic PNC
decoder at the relay. Taking image delivery as an example, experimental results
show that the SC-PNC TWRC achieves high and stable reconstruction quality for
images under different channel conditions and relative phase offsets, compared
with the conventional bit-oriented counterparts
PNC Enabled IIoT: A General Framework for Channel-Coded Asymmetric Physical-Layer Network Coding
This paper investigates the application of physical-layer network coding
(PNC) to Industrial Internet-of-Things (IIoT) where a controller and a robot
are out of each other's transmission range, and they exchange messages with the
assistance of a relay. We particularly focus on a scenario where the controller
has more transmitted information, and the channel of the controller is stronger
than that of the robot. To reduce the communication latency, we propose an
asymmetric transmission scheme where the controller and robot transmit
different amount of information in the uplink of PNC simultaneously. To achieve
this, the controller chooses a higher order modulation. In addition, the both
users apply channel codes to guarantee the reliability. A problem is a
superimposed symbol at the relay contains different amount of source
information from the two end users. It is thus hard for the relay to deduce
meaningful network-coded messages by applying the current PNC decoding
techniques which require the end users to transmit the same amount of
information. To solve this problem, we propose a lattice-based scheme where the
two users encode-and-modulate their information in lattices with different
lattice construction levels. Our design is versatile on that the two end users
can freely choose their modulation orders based on their channel power, and the
design is applicable for arbitrary channel codes.Comment: Submitted to IEEE for possible publicatio
Device Activity Detection in mMTC with Low-Resolution ADC: A New Protocol
This paper investigates the effect of low-resolution analog-to-digital
converters (ADCs) on device activity detection in massive machine-type
communications (mMTC). The low-resolution ADCs induce two challenges on the
device activity detection compared with the traditional setup with assumption
of infinite ADC resolution. First, the codebook design for signal quantization
by the low-resolution ADCs is particularly important since a good codebook
design can lead to small quantization error on the received signal, which in
turn has significant influence on the activity detector performance. To this
end, prior information about the received signal power is needed, which depends
on the number of active devices . This is sharply different from the
activity detection problem in traditional setups, in which the knowledge of
is not required by the BS as a prerequisite. Second, the covariance-based
approach achieves good activity detection performance in traditional setups
while it is not clear if it can still achieve good performance in this paper.
To solve the above challenges, we propose a communication protocol that
consists of an estimator for and a detector for active device identities:
1) For the estimator, the technical difficulty is that the design of the ADC
quantizer and the estimation of are closely intertwined and doing one needs
the information/execution from the other. We propose a progressive estimator
which iteratively performs the estimation of and the design of the ADC
quantizer; 2) For the activity detector, we propose a custom-designed
stochastic gradient descent algorithm to estimate the active device identities.
Numerical results demonstrate the effectiveness of the communication protocol.Comment: Submitted to IEEE for possible publicatio
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