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Description: MIMO OutageCapacity vs SNR
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Size: 1024 |
Author: LD |
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Description: MIMO 系统仿真，对时变信道的自适应调制-erq.m : function for ERQ algorithm in MIMO systems
space_wf.m : function for spatial domain power waterfilling
st_wf.m : function for spatial and temporal domain waterfilling
MIMO_rate.m : Plot spectral efficiency vs SNR for various cases
MIMO_ber.m : Plot BER vs SNR for ERQ algorithm
Report_figN.m : Plot figure N in final report (N=1,2,...,8)
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Size: 18432 |
Author: jonathan Peng |
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Description: 在MIMO-ofdm系统中，空时分组编码STBC对系统性能的测试，给出信噪比和误码率的关系图形。-In the MIMO-ofdm systems, space-time block coding STBC on the system performance test, given the relationship between SNR and bit error rate graphics.
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Size: 22528 |
Author: hquwgz |
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Description: MPSK Modulation Code & BER SNR Calculation
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Size: 81920 |
Author: Ajay |
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Description: ofdm simulation, cantains ber, snr. it s short code ofdm mimo, wimax wide.
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Size: 3072 |
Author: dmowskik |
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Description: SNR plot in rayleigh channel with maximal ratio combining technique for MIMO
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Size: 1024 |
Author: frdownload |
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Description: BER SNR plot in rayleigh channel with maximal ratio combining technique for MIMO
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Size: 3072 |
Author: frdownload |
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Description: 给出了MIMO系统中的通信容量在不同的信噪比中以及在不同的衰落环境中的具体数值-MIMO capacity in various BER
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Size: 1024 |
Author: 李祥东 |
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Description: In this programe a highly scattered enviroment is considered. The Capacity of a MIMO channel with nt transmit antenna and nr recieve antenna is analyzed.capacity of MIMO the result dependences Capacity (bit/s/Hz), and the SNR (dB), in this simulation we used the initial SNR = 2, results of simulation for capacity of MIMO 2x2, 3x3, 4x4 systems
Required Products Communications Toolbox
MATLAB release MATLAB 7.5 (R2007b)
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Size: 1024 |
Author: Rafal |
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Description: 基于期望最大化(EM)的最大后验信道估计算法(MAP)在高信噪比(SNR)下将很难获得较低的估计误差,并且,对于导频辅助的MIMO-OFDM系统,OFDM符号的数据传输效率随着发送天线的增加而明显下降.为改善这两种缺陷,引入一种等效的信号模型来改善高SNR下的估计性能 在相邻多个OFDM符号内使用相移正交导频序列和联合估计来提高系统的数据传输效率和估计性能 根据角域内信道间的独立性来减小噪声对估计的影响.通过仿真实验可知,所提算法具有更小的估计误差和更高的数据传输效率.-Maximum a posteriori(MAP) channel estimation algorithm usually uses expectation maximum(EM) algorithm to decrease the high computation.However,this kind of operation has a difficulty in obtaining ideal estimation performance at high signal to noise ratio(SNR) because of the convergent feature of EM algorithm.In addition,for pilot-based multiple-input multiple-output with orthogonal frequency division multiplexing(MIMO-OFDM) systems,data transmission efficiency of OFDM symbol will be reduced with the increas...
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Size: 134144 |
Author: 王睿 |
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Description: 随着传输速率越来越高,信号所占用的带宽越来越宽,实际信道呈现出频率选择性衰落特
性。根据频率选择性衰落信道特性,建立了频率选择性衰落M IMO信道模型,采用频域和时域的方
法研究了在频率选择性衰落下,发射端已知和未知信道状态信息的M IMO信道容量,并给出了相关
的仿真结果。研究结果表明:在相同发射功率和传输带宽下,M IMO系统可以不牺牲信号带宽而显
著提高信道的容量,并且天线数量和输入信噪比的大小对信道容量具有不同的影响。研究结果为如
何提高频率选择性衰落环境下M IMO信道容量提供了依据。-With the higher and higher of transmitting rate, the signal bandwidth iswider and wider, and the
p ractical channel p resents the frequency selective fading character. In this paper, a multi- input multi-
output (M IMO) channelmodel under frequency selective fading is constructed according to the character of
frequency selective fading channel. The frequency and time domain methods are used to discussM IMO
channel capacity due to the known and unknown channel state information under the frequency selective fa2
ding. The simulation results show thatM IMO system can imp rove the channel capacity remarkably but no
exchanging signal bandwidth under the circumstances of the same launching power and transmitting band2
width, and the numbers of antennas and the quantity of SNR have the different effect on the channel capaci2
ty. The conclusion offers the basis of how to imp rove M IMO channel capacity under the circumstances of
frequency selective fading.
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Size: 513024 |
Author: 蜡笔 |
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Description: 多输入多输出(MIMO)通信系统相比其他的通信系统具有更高的频谱效率，在不增加发射功率以及信号带宽的
情况下，MIMO 技术可以有效地提高系统信道容量及其性能。利用均匀角能量分布以及相关矩阵，分析了相关信道下的MIMO
系统信道容量，得出了系统信道容量的通用公式，并利用MATLAB 进行仿真。仿真结果表明，相关性的增加意味着信噪比的减
小，圆形接收天线阵列半径与角度扩展是决定MIMO 系统信道容量的主要因素。-Multiple-input multiple output (MIMO) communication architecture, as compared with conventional
techniques, has even higher spectral efficiency, and MIMO technique could greatly improve channel capacity and
performance of the system without any increase of transmitting power and bandwidth. By uniform angular distribution
and the correlation matrix, the MIMO channel capacity in correlated channel is investigated. Numerical simulation
is performed with MATLAB, thus to verify the proposed formula. Simulation result indicates that, for this model,
the increase of correlation means the reduction of signal-to-noise ratio (SNR), and the circular receive antenna
array radius or angle spread is the dominating factor for channel capacity.
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Size: 805888 |
Author: 蜡笔 |
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Description: MIMO OFDM 技术将成为第4 代移动通信系统的关键技术, 因MIMO OFDM 对时间和频率偏移非常敏感,
因此MIMO OFDM 同步显得尤为重要。提出了一种新的MIMO OFDM 定时同步和频偏同步技术。以GCL 序列为基础设
计了一个新的符合MIMO OFDM 同步技术的导频序列, 通过对该导频序列进行2 次相关得到频率估计, 并将所得频率
运用到定时同步中, 得到更为准确的时间估计。仿真结果表明, 在相同的信噪比情况下, 该方法可以使得系统的误码
率和帧传送误码率相对传统方法得到进一步减小。-MIMO OFDM will become a key technology of the fourth generation mobile communications system. However, MIMO OFDM is
sensitive to the CFO and timing synchronization, so the MIMO OFDM synchronization technology is very important. This paper proposes an
accurate technique for timing and frequency synchronization of multiple input multiple output ( MIMO ) orthogonal frequency division
multiplexing ( OFDM) systems. The technique derives a new preamble signal based on GCL sequences, according with the MIMJO OFDM
synchronization. The carrier frequency offset ( CFO) estimation is obtained through taking double correlation operations on the preamble signal,
and used in the timing synchronization to gain accurate time estimation. The simulation results show that at the same SNR, the proposed method
can reduce the BER and the frame transmission BER of the system compared to the conventional method.
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Size: 408576 |
Author: 蜡笔 |
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Description: Signal to Noise Ratio in MIMO-OFDM
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Size: 169984 |
Author: Jaanu |
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Description: This program plots the BER vs SNR for a 4X4 MIMO-OFDM system.
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Size: 1024 |
Author: deepa |
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Description: Adaptation in Convolutionally-Coded
MIMO-OFDM Wireless Systems through
Supervised Learning and SNR Ordering
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Size: 1010688 |
Author: nurannisa |
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Description: A 2by3 MIMO model using Simulink. The decoder uses zero forcing algorithm. Set in the workspace the modulation order (QAM modulation), Doppler shift, SNR in dB, bit rate, sample per frame, max number of bits and max number of errors before running the simulation. Works also with BERTool but change the BER variable to ErrorVec. Included in the file a BER session with multiple runs and a figure for several runs.
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Size: 70656 |
Author: flash |
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Description: 此代码是反映，在不同信道比下的MIMO信道容量。-This code is reflected in the different channel than in the MIMO channel capacity.
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Size: 1024 |
Author: 郭鸣霄 |
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Description: 用MATLAB编写的2收2发的带衰落性的信道的MOMO-OFDM(In MATLAB 2-2 of the decaying channel momo-ofdm)
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Size: 1024 |
Author: zhangxiao
|
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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);
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Size: 3933184 |
Author: hlayumi |
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