channel state information

频道状态信息（Channel State Information，简称CSI）是指在无线通信系统中，接收端通过接收到的信号来获取有关发送端和信道之间的信息，包括信道的响应、信道的衰落、信道的干扰等。CSI是无线通信系统中非常重要的参数，可以用于无线信道建模、信道估计、自适应调制等方面。

相关问题

翻译：Notably, the utility functions here do not consider the resource sharing fraction applied in Ye et al. [5]. Instead, we directly use the achievable rate in the utility function. The reasons for this approach are two-fold. First, a UE device can accurately estimate the channel state information (CSI) between itself and a certain BS, but it may not effectively determine the number of devices that are currently being serviced by the BS. Second, the resource allocation strategies adopted by BSs are almost unknown to each UE. Therefore, we remove the resource sharing fraction from the utility function and achieve load balancing based on the access price and the mutual game among BSs.

值得注意的是，这里的效用函数并没有考虑Ye等人在[5]中使用的资源共享比例。相反，我们直接在效用函数中使用可达速率。采取这种方法的原因有两个。首先，用户设备可以准确估计自身与某个基站之间的信道状态信息(CSI)，但可能无法有效确定当前由基站服务的设备数量。其次，基站采用的资源分配策略对每个用户设备几乎是未知的。因此，我们从效用函数中去除了资源共享比例，并基于接入价格和基站之间的博弈实现负载均衡。

将下面matlab代码function [channel] = preRun(acqResults, settings)%% Initialize all channels ================================================ channel = []; % Clear, create the structure channel.PRN = 0; % PRN number of the tracked satellite channel.acquiredFreq = 0; % Used as the center frequency of the NCO channel.codePhase = 0; % Position of the C/A start channel.codeFreq = 0; % Used as the center frequency of the code NCO channel.status = '-'; % Mode/status of the tracking channel % "-" - "off" - no signal to track % "T" - Tracking state %--- Copy initial data to all channels ------------------------------------ channel = repmat(channel, 1, settings.numberOfChannels); %% Copy acquisition results =============================================== %--- Sort peaks to find strongest signals, keep the peak index information [~, PRNindexes] = sort(acqResults.peakMetric, 2, 'descend'); %--- Load information about each satellite -------------------------------- % Maximum number of initialized channels is number of detected signals, but % not more as the number of channels specified in the settings. for ii = 1:min([settings.numberOfChannels, sum(acqResults.carrFreq ~= 0)]) channel(ii).PRN = PRNindexes(ii); channel(ii).acquiredFreq = acqResults.carrFreq(PRNindexes(ii)); channel(ii).codePhase = acqResults.codePhase(PRNindexes(ii)); channel(ii).codeFreq = settings.codeFreqBasis + ... (channel(ii).acquiredFreq - settings.IF)/... settings.carrFreqBasis * settings.codeFreqBasis; % Set tracking into mode (there can be more modes if needed e.g. pull-in) channel(ii).status = 'T'; end转成python

以下是将该 MATLAB 代码转换为 Python 的代码：

import numpy as np

def preRun(acqResults, settings):
    # Initialize all channels
    channel = {}
    channel['PRN'] = 0
    channel['acquiredFreq'] = 0
    channel['codePhase'] = 0
    channel['codeFreq'] = 0
    channel['status'] = '-'

    # Copy initial data to all channels
    channel = [channel] * settings['numberOfChannels']

    # Copy acquisition results
    # Sort peaks to find strongest signals, keep the peak index information
    PRNindexes = np.argsort(acqResults['peakMetric'])[::-1]

    # Load information about each satellite
    # Maximum number of initialized channels is number of detected signals, but
    # not more as the number of channels specified in the settings.
    for ii in range(min(settings['numberOfChannels'], sum(acqResults['carrFreq'] != 0))):
        channel[ii]['PRN'] = PRNindexes[ii]
        channel[ii]['acquiredFreq'] = acqResults['carrFreq'][PRNindexes[ii]]
        channel[ii]['codePhase'] = acqResults['codePhase'][PRNindexes[ii]]
        channel[ii]['codeFreq'] = settings['codeFreqBasis'] + \
            (channel[ii]['acquiredFreq'] - settings['IF']) / \
            settings['carrFreqBasis'] * settings['codeFreqBasis']
        # Set tracking into mode (there can be more modes if needed e.g. pull-in)
        channel[ii]['status'] = 'T'

    return channel