release 10 pdsch enhanced ue-凯发k8网页登录

rmc = struct;                      % rmc config structure
rmc.rc ='r.5';                     % base configuration on rmc r.5
rmc.duplexmode = 'tdd';            % user time division duplex (tdd)
rmc.totsubframes = 1;              % configure a single subframe
% generate the base configuration from rmc r.5 and amend to set the
% parameters required for the port7-14 transmission scheme. note that if
% the standard defined rmcs using port7-14 transmission scheme supported by
% ltermcdl is used, these parameters will be pre-configured.
rmc = ltermcdl(rmc);
rmc.ndlrb = 25;                    % 25 resource blocks
rmc.ncellid = 10;                  % cell identity 10
rmc.pdsch.txscheme = 'port7-14';   % up to 8 layer transmission, ports 7-14
rmc.pdsch.nlayers = 2;             % 2 transmission layers for beamforming
rmc.pdsch.nscid = 0;               % scrambling identity 0
rmc.csirefp = 8;                   % 8 csi-rs ports
rmc.csirsconfig = 0;               % csi-rs configuration 0
rmc.csirsperiod = 'on';            % configure csi-rs always 'on'
rmc.zeropowercsirsperiod = 'off';  % configure zero power csi-rs 'off'
rmc.pdsch.prbset = (4:8).';        % 5 allocated rbs
rmc.pdsch.pmimode = 'wideband';    % wideband pmi mode
rmc.pdsch.csi = 'on';              % csi scaling of soft bits
% codebook subset definition allowing all codebook entries
rmc.pdsch.codebooksubset = '0x1fffffffffffffffffffffffffff';

channel = struct;                   % channel config structure
channel.seed = 8;                   % channel seed
channel.nrxants = 3;                % 3 receive antennas
channel.delayprofile = 'eva';       % delay profile
channel.dopplerfreq = 5.0;          % doppler frequency in hz
channel.mimocorrelation = 'medium'; % multi-antenna correlation
channel.nterms = 16;                % oscillators used in fading model
channel.modeltype = 'gmeds';        % rayleigh fading model type
channel.inittime = 0.0;             % initial time
channel.initphase = 'random';       % random initial phases
channel.normalizepathgains = 'on';  % normalize delay profile power
channel.normalizetxants = 'on';     % normalize for transmit antennas

cec = struct;                       % channel estimation config structure
cec.pilotaverage = 'userdefined';   % type of pilot symbol averaging
cec.freqwindow = 1;                 % frequency window size (special mode)
cec.timewindow = 2;                 % time window size (special mode)
cec.interptype = 'cubic';           % 2d interpolation type
cec.interpwindow ='centered';       % interpolation window type
cec.interpwinsize = 1;              % interpolation window size

% transmit without then with csi-rs-based pmi feedback
for csirsfeedback = 0:1
    % configure random number generators
    rng('default');
    % configure pdsch substructure with transmission beamforming matrix w.
    % in the first iteration of the loop transmit each layer on one of the
    % 8 antennas. in the second iteration, transmit the layers on 2 beams
    % matched to the channel response using csi-rs-based pmi feedback. the
    % pmi fed back to the second iteration is calculated at the end of the
    % first
    if ~csirsfeedback
        rmc.pdsch.w = [1 0 0 0 0 0 0 0; ...
                       0 0 0 0 1 0 0 0]/sqrt(2);
    else
        rmc.pdsch.w = ltecsicodebook(rmc.pdsch.nlayers, ...
                                     rmc.csirefp, [pmi(1) pmi(2)]).';
    end
    % generate transmission with pdsch with the beamforming matrix w, onto
    % 1st of 8 antenna planes (note that cellrefp = 1 for this rmc). the
    % transmitted grid contains ue-specific reference signal (ue-rs / dmrs)
    % for channel estimation and csi-rs reference signal for pmi selection
    [~, txgrid, rmcinfo] = ltermcdltool(rmc, [1;0;0;1]);
    channel.samplingrate = rmcinfo.samplingrate;
    % ofdm modulation. the additional 25 samples added to the end of the
    % waveform are to cover the range of delays expected from the channel
    % modeling (a combination of implementation delay and channel delay
    % spread)
    [txwaveform, ofdmdims] = lteofdmmodulate(rmc, txgrid, 0);
    txwaveform = [txwaveform; zeros(25, size(txwaveform,2))]; %#ok
    % fading channel
    rxwaveform = ltefadingchannel(channel, txwaveform);
    % create and apply additive white gaussian noise
    if ~csirsfeedback
        snrdb = 27;
        snr = 10^(snrdb/20);
        n = 1/(sqrt(2.0*rmc.csirefp*double(ofdmdims.nfft))*snr);
        v = n*complex(randn(size(rxwaveform)), randn(size(rxwaveform)));
    end
    rxwaveform = rxwaveform   v;
    % perform synchronization
    offset = ltedlframeoffset(rmc, rxwaveform);
    rxwaveform = rxwaveform(1 offset:end, :);
    % perform ofdm demodulation on the received data to recreate the
    % resource grid
    rxgrid = lteofdmdemodulate(rmc, rxwaveform);
    % channel estimation using the ue-specific dmrs for pdsch reception
    cec.reference = 'dmrs';
    [hest, nest] = ltedlchannelestimate(rmc, rmc.pdsch, cec, rxgrid);
    % equalize (back to layers) and demodulate the pdsch.
    % extract res corresponding to the 2 layers of the pdsch from the given
    % subframe across all receive antennas and channel estimates.
    ind = ltepdschindices(rmc, rmc.pdsch, rmc.pdsch.prbset);
    [pdschrx, pdschhest] = lteextractresources(ind, rxgrid, hest);
    [rxbits, rxsymbols] = ltepdschdecode(rmc, rmc.pdsch, ...
        pdschrx, pdschhest, nest);
    % compute singular values of the channel and calculate snr
    h = squeeze(mean(pdschhest));
    d = svd(h);
    % print singular values and effective channel snr
    if csirsfeedback
        label = '8 antenna transmission with csi-rs-based pmi feedback';
    else
        label = '8 antenna transmission, 1 antenna for each layer';
    end
    fprintf('%s:\n\n', label);
    svdb = sprintf('     %0.2fdb', 20*log10(d));
    fprintf('       channel singular values:%s\n', svdb);
    fprintf('         effective channel snr:     %0.2fdb\n', ...
        snrdb 10*log10(rmc.pdsch.nlayers) 10*log10(sum(d.^2)));
    % regenerate pdsch from hard bit decisions and demodulate to estimate
    % transmitted symbols
    remod = ltepdsch(rmc, rmc.pdsch, rxbits{1}>0);
    [rxbitsref, rxsymbolsref] = ltepdschdecode(rmc, rmc.pdsch, remod);
    % use evm measurement to estimate snr
    evm = comm.evm;
    evmrms = evm(rxsymbolsref{1},rxsymbols{1});
    snrest = 20*log10(1/(evmrms/100));
    fprintf('snr estimate from receiver evm:     %0.2fdb\n\n',snrest);
    % now compute pmi (via csi-rs) for use in second iteration. channel
    % realization remains the same
    if ~csirsfeedback
        % channel estimation via csi-rs for pmi selection
        cec.reference = 'csirs';
        [hestpmi, nestpmi] = ltedlchannelestimate(rmc, rmc.pdsch, ...
            cec, rxgrid);
        % pmi selection
        pmi = ltepmiselect(rmc, rmc.pdsch, hestpmi, nestpmi);
    end
    % plot received constellation
    figure(csirsfeedback 1);
    plot(rxsymbols{1}, 'o', 'markeredgecolor', [0.75 0 0], ...
        'markerfacecolor', [1 0.25 0.25], 'markersize',3);
    axis([-1.25 1.25 -1.25 1.25]);
    title(label);
end