12,567 research outputs found
Dynamical interpretation of the wavefunction of the universe
In this paper, we study the physical meaning of the wavefunction of the
universe. With the continuity equation derived from the Wheeler-DeWitt (WDW)
equation in the minisuperspace model, we show that the quantity
for the universe is inversely proportional to the Hubble
parameter of the universe. Thus, represents the probability density
of the universe staying in the state during its evolution, which we call
the dynamical interpretation of the wavefunction of the universe. We
demonstrate that the dynamical interpretation can predict the evolution laws of
the universe in the classical limit as those given by the Friedmann equation.
Furthermore, we show that the value of the operator ordering factor in the
WDW equation can be determined to be
Integrated Sensing, Computation, and Communication: System Framework and Performance Optimization
Integrated sensing, computation, and communication (ISCC) has been recently
considered as a promising technique for beyond 5G systems. In ISCC systems, the
competition for communication and computation resources between sensing tasks
for ambient intelligence and computation tasks from mobile devices becomes an
increasingly challenging issue. To address it, we first propose an efficient
sensing framework with a novel action detection module. It can reduce the
overhead of computation resource by detecting whether the sensing target is
static. Subsequently, we analyze the sensing performance of the proposed
framework and theoretically prove its effectiveness with the help of the
sampling theorem. Then, we formulate a sensing accuracy maximization problem
while guaranteeing the quality-of-service (QoS) requirements of tasks. To solve
it, we propose an optimal resource allocation strategy, in which the minimal
resource is allocated to computation tasks, and the rest is devoted to sensing
tasks. Besides, a threshold selection policy is derived. Compared with the
conventional schemes, the results further demonstrate the necessity of the
proposed sensing framework. Finally, a real-world test of action recognition
tasks based on USRP B210 is conducted to verify the sensing performance
analysis, and extensive experiments demonstrate the performance improvement of
our proposal by comparing it with some benchmark schemes
Joint Transceiver Design for Dual-Functional Full-Duplex Relay Aided Radar-Communication Systems
Driven by the demand for massive and accurate sensing data to achieve wireless network intelligence under a limited available spectrum, the coexistence between radar and communication systems has attracted public attention. In this paper, we investigate a novel dual-functional full-duplex relay aided radar-communication system where the phased-array radar is employed at the amplify-and-forward (AF) relay. A joint transceiver design is proposed to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all detection directions at the radar receiver under communication quality-of-service and total energy constraints. The formulated optimization problem is particularly challenging due to the highly nonconvex objective function and constraints. Based on the problem structure, we equivalently decompose it into the radar-energy and relay-energy minimization problems under SINR requirements. To solve the radar-energy minimization problem, we propose a low-complexity algorithm based on the alternating direction method of multipliers to optimize the radar transmit power and receiver. The relay-energy minimization problem can be simplified into an equivalent quadratic programming problem by introducing an insightful unitary matrix. Then, the closed-form expression for the AF relay beamforming matrix can be derived, which is jointly determined by the channel condition of relay communication and the detection direction of the radar. After that, we introduce the overall transceiver design algorithm to the original problem and discuss its optimality and computational complexity. Simulation results verify that the proposed algorithm significantly outperforms other benchmark algorithms
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