Abstract
Orbital angular momentum (OAM) has been a popular topic due to the natural orthogonality of OAM waves with different modes. It is expected to greatly improve the channel capacity of wireless communication systems. From the perspective of networking, this letter proposes an OAM-based different modes networking method (OAM DMN) that sets adjacent cells with OAM carriers of different modes, so as to improve the signal quality and spectrum efficiency of wireless network and better adapt to the high-density base station distribution scenario. This letter firstly analyzes the characteristics of atmospheric channel on OAM waves by regarding turbulent as random phase screen based on Kolmogorov turbulence theory. Combining with stochastic geometry, we get the outage probability function of wireless cells. Then two types of OAM DMN schemes are proposed to test the performance of the network under different channel conditions. Simulation shows that OAM DMN wireless network has lower outage probability compared with other OAM-based and conventional networks and better performance on high-density base station distribution.
Highlights
T HE orbital angular momentum wave has a spiral wavefront exp(−ilφ) whose shape is determined by mode l, where l can take any integer[1]
We proposed a Orbital angular momentum (OAM) DMN method so as to explore the feasibility of using OAM in wireless networking
We studied atmospheric turbulence model’s influence on the spiral phase of OAM wave by directly correlating with the Kolmogorov turbulence theory, which we converted turbulence into random phase screen
Summary
When OAM waves propagate in atmospheric turbulence, helical phase distortion will occur, resulting in the loss of orthogonality. (1) An OAM-based different modes networking method (OAM DMN) for wireless network is proposed, which sets adjacent cells with OAM carriers of different modes to send cell signal. (2) A new random atmospheric channel model is proposed by combining amplitude fading and spiral phase distortion, where we directly change the influence of atmospheric. We get the outage probability function of wireless cells by combining stochastic base station distribution and random atmospheric channel model. Simulation results show that OAM DMN gets better performance on signal quality and adapting to highdensity base station scenarios
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