1,373 research outputs found
Size effect of Ruderman-Kittel-Kasuya-Yosida interaction mediated by electrons in nanoribbons
We calculated the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction between
the magnetic impurities mediated by electrons in nanoribbons. It was shown that
the RKKY interaction is strongly dependent on the width of the nanoribbon and
the transverse positions of the impurities. The transverse confinement of
electrons is responsible for the above size effect of the RKKY interaction. It
provides a potential way to control the RKKY interaction by changing
nanostructure geometry
Joint Beam Direction Control and Radio Resource Allocation in Dynamic Multi-beam LEO Satellite Networks
Multi-beam low earth orbit (LEO) satellites are emerging as key components in
beyond 5G and 6G to provide global coverage and high data rate. To fully
unleash the potential of LEO satellite communication, resource management plays
a key role. However, the uneven distribution of users, the coupling of
multi-dimensional resources, complex inter-beam interference, and time-varying
network topologies all impose significant challenges on effective communication
resource management. In this paper, we study the joint optimization of beam
direction and the allocation of spectrum, time, and power resource in a dynamic
multi-beam LEO satellite network. The objective is to improve long-term user
sum data rate while taking user fairness into account. Since the concerned
resource management problem is mixed-integer non-convex programming, the
problem is decomposed into three subproblems, namely beam direction control and
time slot allocation, user subchannel assignment, and beam power allocation.
Then, these subproblems are solved iteratively by leveraging matching with
externalities and successive convex approximation, and the proposed algorithms
are analyzed in terms of stability, convergence, and complexity. Extensive
simulations are conducted, and the results demonstrate that our proposal can
improve the number of served users by up to two times and the sum user data
rate by up to 68%, compared to baseline schemes.Comment: Accepted by IEEE Transactions on Vehicular Technolog
Improved Model Predictive Current Control for SPMSM Drives With Parameter Mismatch
Model predictive current control (MPCC) can predict future motor behavior according to a motor model. In practice, however, motor parameters will vary at run time, and the parameter mismatch disturbances caused by the variation in motor parameters will deteriorate the MPCC performance. To suppress the parameter mismatch disturbances effectively, this paper proposes a modified MPCC with a current variation update mechanism. In contrast with the traditional current prediction equation that contains crude model parameters, the modified current prediction equation contains only measured information, taking advantage of the proposed current variation update mechanism, which can update the modified prediction equation within each sampling period. A simulation established by MATLAB software indicates that the proposed method can effectively suppress the parameter mismatch disturbances. Experiments are carried out to verify the correctness of the proposed method
Joint Network Function Placement and Routing Optimization in Dynamic Software-defined Satellite-Terrestrial Integrated Networks
Software-defined satellite-terrestrial integrated networks (SDSTNs) are seen
as a promising paradigm for achieving high resource flexibility and global
communication coverage. However, low latency service provisioning is still
challenging due to the fast variation of network topology and limited onboard
resource at low earth orbit satellites. To address this issue, we study service
provisioning in SDSTNs via joint optimization of virtual network function (VNF)
placement and routing planning with network dynamics characterized by a
time-evolving graph. Aiming at minimizing average service latency, the
corresponding problem is formulated as an integer nonlinear programming under
resource, VNF deployment, and time-slotted flow constraints. Since exhaustive
search is intractable, we transform the primary problem into an integer linear
programming by involving auxiliary variables and then propose a Benders
decomposition based branch-and-cut (BDBC) algorithm. Towards practical use, a
time expansion-based decoupled greedy (TEDG) algorithm is further designed with
rigorous complexity analysis. Extensive experiments demonstrate the optimality
of BDBC algorithm and the low complexity of TEDG algorithm. Meanwhile, it is
indicated that they can improve the number of completed services within a
configuration period by up to 58% and reduce the average service latency by up
to 17% compared to baseline schemes.Comment: Accepted by IEEE Transactions on Wireless Communication
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