Communication channel

About: Communication channel is a research topic. Over the lifetime, 137411 publications have been published within this topic receiving 1715077 citations. The topic is also known as: communication channel & communications channel.

Blind channel identification based on second-order statistics: a frequency-domain approach

Abstract: In this communication, necessary and sufficient conditions are presented for the unique blind identification of possibly nonminimum phase channels driven by cyclostationary processes. Using a frequency domain formulation, it is first shown that a channel can be identified by the second-order statistics of the observation if and only if the channel transfer function does not have special uniformly spaced zeros. This condition leads to several necessary and sufficient conditions on the observation spectra and the channel impulse response. Based on the frequency-domain formulation, a new identification algorithm is proposed. >

A Comprehensive Survey on UAV Communication Channel Modeling

Abstract: Unmanned aerial vehicles (UAVs) have stroke great interested both by the academic community and the industrial community due to their diverse military applications and civilian applications. Furthermore, UAVs are also envisioned to be part of future airspace traffic. The application functions delivery relies on information exchange among UAVs as well as between UAVs and ground stations (GSs), which further closely depends on aeronautical channels. However, there is a paucity of comprehensive surveys on aeronautical channel modeling in line with the specific aeronautical characteristics and scenarios. To fill this gap, this paper focuses on reviewing the air-to-ground (A2G), ground-to-ground (G2G), and air-to-air (A2A) channel measurements and modeling for UAV communications and aeronautical communications under various scenarios. We also provide the design guideline for managing the link budget of UAV communications taking account of link losses and channel fading effects. Moreover, we also analyze the receive/transmit diversity gain and spatial multiplexing gain achieved by multiple-antenna-aided UAV communications. Finally, we discuss the remaining challenge and open issues for the future development of UAV communication channel modeling.

Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning

Abstract: In federated learning (FL), devices contribute to the global training by uploading their local model updates via wireless channels. Due to limited computation and communication resources, device scheduling is crucial to the convergence rate of FL. In this paper, we propose a joint device scheduling and resource allocation policy to maximize the model accuracy within a given total training time budget for latency constrained wireless FL. A lower bound on the reciprocal of the training performance loss, in terms of the number of training rounds and the number of scheduled devices per round, is derived. Based on the bound, the accuracy maximization problem is solved by decoupling it into two sub-problems. First, given the scheduled devices, the optimal bandwidth allocation suggests allocating more bandwidth to the devices with worse channel conditions or weaker computation capabilities. Then, a greedy device scheduling algorithm is introduced, which selects the device consuming the least updating time obtained by the optimal bandwidth allocation in each step, until the lower bound begins to increase, meaning that scheduling more devices will degrade the model accuracy. Experiments show that the proposed policy outperforms state-of-the-art scheduling policies under extensive settings of data distributions and cell radius.

"Turbo DPSK": iterative differential PSK demodulation and channel decoding

Abstract: Multiple symbol differential detection is known to fill the gap between conventional differential detection of MPSK (M-DPSK) and coherent detection of M-PSK with differential encoding (M-DEPSK). Emphasis has been so far on soft-input/hard-output detectors applied in uncoded systems. In this paper, we investigate a receiver structure suitable for coded DPSK signals on static and time-varying channels. The kernel is an a posteriori probability (APP) DPSK demodulator. This demodulator accepts a priori information and produces reliability outputs. Due to the availability of reliability outputs, an outer soft-decision channel decoder can be applied. Due to the acceptance of a priori information, if the outer channel decoder also outputs reliability information, iterative ("turbo") processing can be done. The proposed "APP DPSK demodulator" uses linear prediction and per-survivor processing to estimate the channel response. The overall transmission scheme represents a type of serial "turbo code," with a differential encoder concatenated with a convolutional code, separated by interleaving. The investigated system has the potential to improve the performance of coherent PSK without differential encoding and perfect channel estimation for fading cases! Only a small number of iterations are required. The receiver under investigation can be applied to several existing standards without changing the transmission format. Results are presented for uncoded and convolutionally coded 4-DPSK modulation transmitted over the Gaussian channel and the Rayleigh flat-fading channel, respectively.