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Description: Joint maximum likelihood (ML)symbol-time and carrier-frequency offset estimator in orthogonal frequency-division multiplexing(OFDM) systems.-Joint maximum likelihood (ML)symbol-time and carrier-frequency offset estimator in orthogonal frequency-division multiplexing(OFDM) systems.
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Size: 136192 |
Author: jenna |
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Description: 基于STBC的ML检测MIMO仿真,可以完成ML联合STBC仿真。-The ML detection of MIMO STBC-based simulation, simulation can be completed ML joint STBC.
Platform: |
Size: 7168 |
Author: 刘毅 |
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Description: 一篇非常实用的无线通信方向的文献，是关于cdma系统中doa估计的经典-The use of antenna arrays in wireless communications
makes it possible to estimate the directions of arrival (DOAs)
of impinging waveforms. The latter can be exploited to enhance
channel estimation accuracy or as an input for advanced mobile
positioning systems. In this paper, we consider the uplink of a
multicarrier code-division multiple-access (MC-CDMA) network
in which the base station is endowed with multiple receiving antennas
arranged in a uniform linear array. Transmission takes place
over a multipath channel, and the goal is the joint estimation of
the channel responses and DOAs of the uplink signals. In doing so,
we follow a maximum-likelihood (ML) approach and assume that
users transmit orthogonal training sequences to facilitate the task
of separating the signals. This way, all unknown parameters are
estimated independently of each other with affordable complexity.
Theoretical analysis and computer simulations are used to assess
the performance of the propose
Platform: |
Size: 249856 |
Author: Zhang Lin |
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Description: 基于ML的OFDM定时和载波联合估计算法-joint timing and carrierestimation algorithm Based on ML for OFDM system
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Size: 1024 |
Author: 王大青 |
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Description: we present a new space–time block code for timeand frequency-selective (doubly-selective) channels. It can be interpreted
as the extension of the Alamouti code to doubly-selective channels, and relies on a joint time–frequency reversal of the transmitted sequences. Under
certain channel conditions, the proposed space–time block code belongs
to the class that achieves full spatial, delay, and Doppler diversity using a
maximum-likelihood (ML) receiver, as well as a linear zero-forcing (LZF)
or linear minimum mean-squared error (LMMSE) receiver. For realistic
doubly-selective channels, a real-valued linear data model is presented, for
which different receiver structures can be developed.
Platform: |
Size: 1024 |
Author: phuong |
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Description: % Type of different detectors, parameters for Detector.m
ML = 1; % Joint ML Detector
JMMSE = 2; % Joint MMSE Detector
ZF = 3; % Joint Zero-Forcing Detector
% Type of different antenna selection criteria methods
MBER = 1;
MMI = 2;
LAZY = 3;
MNP = 4; %Minimum Noise Power
MMNP = 5;
LAZY2 = 6;
real_ch = 0; % real_ch = 0 refers to simulated channel in MATLAB, otherwise refers to real channel
SNR_dB = 20;% transmit SNR in the simulated channel
nr_frames = 20; % number of frames sent when simulation.
detect_type = ZF; % Detector choice
select_type = MBER; % Antenna selection choice
disp('');
tx(nr_frames);
disp('Press any key to continue');
pause
RF(real_ch,SNR_dB);
disp('Press any key to continue');
pause
BER = rx(detect_type,select_type);
Platform: |
Size: 3933184 |
Author: hlayumi |
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