Interference (wave propagation)

About: Interference (wave propagation) is a research topic. Over the lifetime, 26086 publications have been published within this topic receiving 321110 citations.

Iterative multiuser detection using antenna arrays and FEC on multipath channels

Abstract: This paper investigates a multiple-access communication receiver system that receives coded data modulated using either direct-sequence code division multiple access or narrowband binary phase shift keying, with an antenna array in a multipath propagation environment. We describe an iterative receiver that improves the initial estimates from the antenna array, and therefore reduces the multiple access interference. Simulation results show that the bit error rate performance approaches that obtained when only one user's signal is incident on the array. This occurs even with a large number of users in comparison to the product of the spreading gain and array size.

Method for amplitude insensitive packet detection

Abstract: The invention relates generally to the field of wireless communications and more particularly to a method of and device for detecting the presence of a received data packet in a digital receiver. The present invention proposes a simplified method of correlation by removing dependency on the amplitude fluctuations while at the same time maintaining phase relevancy. The key advancement involves mapping the complex quadrature amplitude modulation (QAM) preamble to a quantized phase shift keying (PSK) constellation before application to a matched complex correlator. The proposed process essentially “amplitude normalizes” the input signal without the use or complexity associated with a divider. This simplified normalization scheme makes the packet detection algorithm robust against amplitude variations in the input signal, while still allowing for good correlation output. In applications where interference is superimposed on the I/Q input signals, the invention improves the detection capability over automatic gain control (AGC) normalization methods.

A law of interference of electromagnetic beams of any state of coherence and polarization and the Fresnel-Arago interference laws

Abstract: A new general interference law is derived for the superposition of two random electromagnetic beams of any state of coherence and of any state of polarization when the beams are transmitted through polarizers and rotators. It includes, as special cases, a variety of interference laws that apply to particular situations. Some of them have a close bearing on the classic interference experiments of Fresnel and Arago that have played a basic role in elucidating the concept of polarization of light.

Interference measurement mechanism for frequency reuse in cellular ofdma systems

Abstract: Under adaptive frequency reuse technique, mobile stations in a cellular orthogonal frequency division multiple access (OFDMA) system are served by different radio resource regions with appropriate frequency reuse patterns to mitigate inter-cell interference and improve system capacity. In a first novel aspect, the mobile stations measure interference statistics and obtain interference measurement results. The mobile stations report the obtained interference measurement results to serving base stations. The serving base stations determine adaptive frequency reuse patterns based on the received interference measurement result. In a second novel aspect, a radio resource control element receives the interference measurement results, determines frequency reuse patterns and configures radio resource allocation based on the received interference measurement results. In a third novel aspect, the base stations obtain the interference measurement results and schedule the mobile stations to be served with appropriate radio resource regions.

Reinforcement Learning-Based Downlink Interference Control for Ultra-Dense Small Cells

Abstract: The dense deployment of small cells in 5G cellular networks raises the issue of controlling downlink inter-cell interference under time-varying channel states. In this paper, we propose a reinforcement learning based power control scheme to suppress downlink inter-cell interference and save energy for ultra-dense small cells. This scheme enables base stations to schedule the downlink transmit power without knowing the interference distribution and the channel states of the neighboring small cells. A deep reinforcement learning based interference control algorithm is designed to further accelerate learning for ultra-dense small cells with a large number of active users. Analytical convergence performance bounds including throughput, energy consumption, inter-cell interference, and the utility of base stations are provided and the computational complexity of our proposed scheme is discussed. Simulation results show that this scheme optimizes the downlink interference control performance after sufficient power control instances and significantly increases the network throughput with less energy consumption compared with a benchmark scheme.