Description: matlab code from book"MIMO signals and systems"-matlab code from book MIMO signals and systems Platform: |
Size: 14336 |
Author:dingjun |
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Description: MIMO Signals And Systems一书的Matlab程序。-MIMO Signals And Systems of a book on Matlab procedures. Platform: |
Size: 15360 |
Author:cyhgxu |
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Description: MIMO信号与系统英文书里面配套的matlab程序，包括Alamouti原理的空时块码接收机过程等等。-MIMO Signals and Systems in English inside the book matching matlab procedures, including the principle of Alamouti space-time block code receiver process and so on. Platform: |
Size: 16384 |
Author:aiguixia |
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Description: Euler方法 用C语言实现，并求解常微分方程组-The m framework appropriately generalizes notions such as gain margin, phase
margin, disturbance attenuation, tracking, and noise rejection into a common
framework suitable for analysis and design, in both single-loop and multiloop
feedback systems. Even when working with single-loop feedback systems, some
multi-input, multi-output (MIMO) systems arise during the analysis. Hence, a
unified framework to deal with MIMO linear systems is important, with full
support for both the time and frequency domain. m-Tools provides the
capability to build complex interconnections (such as cascade, parallel, and
feedback connections), compute properties (such as poles and zeros), calculate
time and frequency responses, manipulate these responses (FFT for the time
domain signals, Bode analysis for the frequency domain functions), and plot
results. m-Tools supports two data types in addition to the standard matrices:
SYSTEM matrices for state-space realizations Platform: |
Size: 1024 |
Author:落思 |
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Description: As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM)
technique can achieve high data rate in frequency-selective fading channels by splitting a
broadband signal into a number of narrowband signals over a number of subcarriers, where
each subcarrier is more robust to multipath. The wireless communication system with multiple
antennas at both the transmitter and receiver, known as multiple-input multiple-output
(MIMO) system, achieves high capacity by transmitting independent information over different
antennas simultaneously. The combination of OFDM with multiple antennas has been
considered as one of most promising techniques for future wireless communication systems. Platform: |
Size: 2609152 |
Author:ashish |
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Description: Multiple input multiple output techniques combined
with orthogonal frequency division multiplexing (MIMO-OFDM)
provide a promising approach for wireless systems. However, a
serious drawback of the OFDM system is the high peak-toaverage
power ratio (PAPR), which may severely affect the
power efficiency of RF power amplifiers. In this paper, we
propose a simple method to reduce the PAPR of MIMO-OFDM
signals based on the use of unused subcarriers. Instead of
processing the signals at each transmitter separately, a peak
cancelling signal is generated at one antenna and is then applied
to all the others with only simple modifications. Simulation has
shown that a minimum 2 dB reduction in PAPR can be achieved
for all transmit signals using this approach. As the signal
processing is nearly all done at a single transmitter, repetition of
the operations at each transmitter is avoided, and therefore the
overall cost of the system can be significantly reduced. Platform: |
Size: 714752 |
Author:payal |
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Description: Multiple input multiple output techniques combined
with orthogonal frequency division multiplexing (MIMO-OFDM)
provide a promising approach for wireless systems. However, a
serious drawback of the OFDM system is the high peak-toaverage
power ratio (PAPR), which may severely affect the
power efficiency of RF power amplifiers. In this paper, we
propose a simple method to reduce the PAPR of MIMO-OFDM
signals based on the use of unused subcarriers. Instead of
processing the signals at each transmitter separately, a peak
cancelling signal is generated at one antenna and is then applied
to all the others with only simple modifications. Simulation has
shown that a minimum 2 dB reduction in PAPR can be achieved
for all transmit signals using this approach. As the signal
processing is nearly all done at a single transmitter, repetition of
the operations at each transmitter is avoided, and therefore the
overall cost of the system can be significantly reduced. Platform: |
Size: 5120 |
Author:payal |
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Description: MIMO Signals and Systems，这本书籍的附带程序，非常经典，适合初学者使用- MIMO Signals and Systems, this book comes with the program, very classic, suitable for beginners Platform: |
Size: 17408 |
Author:maomao |
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Description: MIMO信号系统经典书籍MIMO Signals and Systems
-The MIMO signal system classic books MIMO Signals and Systems Platform: |
Size: 603136 |
Author:qiqi |
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Description: 本文在介绍MIMO无线通信系统模型的基础上，通过对比分析几种常用空时编码方法，选定空时分组码对信号进行编码并建立瑞利衰落信道模型，通过对两发一收及两发两收系统的仿真，研究接收天线数对系统接收信号可靠性的影响。之后进一步扩展到不同发射矩阵条件下研究多发一收系统的频谱利用率及误符号率，分析不同天线数目，不同发射矩阵条件下空时正交分组码检测算法的性能。-This paper introduced the MIMO wireless communication system model, through the comparative analysis of several commonly used method of space-time coding, grouping code for the selected space-time signal is encoded and establish Rayleigh fading channel model, through two rounds one and two rounds of closing Simulation of two closed systems, research receiving antennas to receive signals affect the reliability of the system. After further extended to study the conditions under different emission matrix of multiple spectral efficiency and symbol error rate of a closed system, analyze the different number of antennas, the performance under different emission matrix orthogonal space-time block codes condition detection algorithm. Platform: |
Size: 576512 |
Author:starcool |
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Description: MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE,
Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n),
wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). This book provides a
comprehensive introduction to the basic theory and practice of wireless channel modeling,
OFDM, and MIMO, with MATLAB programs to simulate the underlying techniques on
MIMO-OFDM systems. This book is primarily designed for engineers and researchers who are
interested in learning various MIMO-OFDM techniques and applying them to wireless
communications. It can also be used as a textbook for graduate courses or senior-level
undergraduate courses on advanced digital communications. The readers are assumed to have
a basic knowledge on digital communications, digital signal processing, communication
theory, signals and systems, as well as probability and random processes. Platform: |
Size: 11264000 |
Author:Robin |
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Description: If SDMA is used on the downlink of a multi-user MIMO system,
either long-term or short-term channel state information
has to be available at the base station (BS) to faciliate the joint
precoding of the signals intended for the different users. Precoding
is used to efficiently eliminate or suppressmulti-user interference
(MUI) via beamforming or by using ”dirty-paper”
codes. It also allows us to performmost of the complex processing
at the BS which leads to a simplification of the mobile terminals.
In this paper, we provide an overview of efficient linear
and non-linear precoding techniques formulti-userMIMO
systems. The performance of these techniques is assessed via
simulations on statistical channelmodels, and on channels generated
by the IlmProp, a geometry-based channel model that
generates realistic correlations in space, time, and frequency. Platform: |
Size: 74752 |
Author:ImranKhan |
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Description: MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE,
Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n),
wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). This book provides a
comprehensive introduction to the basic theory and practice of wireless channel modeling,
OFDM, and MIMO, with MATLAB programs to simulate the underlying techniques on
MIMO-OFDM systems. This book is primarily designed for engineers and researchers who are
interested in learning various MIMO-OFDM techniques and applying them to wireless
communications. It can also be used as a textbook for graduate courses or senior-level
undergraduate courses on advanced digital communications. The readers are assumed to have
a basic knowledge on digital communications, digital signal processing, communication
theory, signals and systems, as well as probability and random processes. Platform: |
Size: 5013504 |
Author:werad |
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Description: Abstract—Diagonal Bell Laboratories Layered Space-Time (DBLAST)
structure offers a low complexity solution to realize the
attractive capacity of Multiple-input and multiple-output (MIMO)
systems. In this paper, we apply D-BLAST in orthogonal frequency
division multiplexing (OFDM) systems and address the issue of
channel estimation. Different other MIMO-OFDM, where
symbols at all tones are always available for decision-directed
channel estimation, in D-BLAST OFDM, we update estimated
channel parameters each time a layer is detected with a least
square (LS) approach, using a pieced combination of received signals
at previous and current OFDM blocks. The initial estimate is
further refined by a robust estimator to exploit the time correlation
of channel parameters among OFDM blocks. Computer simulation
results show the performance improvement over block-wise
channel estimation. It is also shown that D-BLAST with proposed
channel estimation is robust to fast fading of channel parameters.-Abstract—Diagonal Bell Laboratories Layered Space-Time (DBLAST)
structure offers a low complexity solution to realize the
attractive capacity of Multiple-input and multiple-output (MIMO)
systems. In this paper, we apply D-BLAST in orthogonal frequency
division multiplexing (OFDM) systems and address the issue of
channel estimation. Different other MIMO-OFDM, where
symbols at all tones are always available for decision-directed
channel estimation, in D-BLAST OFDM, we update estimated
channel parameters each time a layer is detected with a least
square (LS) approach, using a pieced combination of received signals
at previous and current OFDM blocks. The initial estimate is
further refined by a robust estimator to exploit the time correlation
of channel parameters among OFDM blocks. Computer simulation
results show the performance improvement over block-wise
channel estimation. It is also shown that D-BLAST with proposed
channel estimation is robust to fast fading of channel parameters. Platform: |
Size: 80896 |
Author:werad |
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Description: 可见光通信是通过驱动电路将电信号转换成光信号并通过LED 发射出去，接收端通过光检测设备接收光信号，并提取其中有用的信号分量，从而实现通信。
研究OFDM和MIMO的关键技术，并针对室内可见光通信系统提出合适的MIMO-OFDM 方案。(isible light communication is through the drive circuit converts electrical signals into light signals and transmitted through LED, the receiving end through the optical detection device receives the light signal, and extract the useful signal component, so as to achieve communication.
The key technologies of OFDM and MIMO are studied, and an appropriate MIMO-OFDM scheme is proposed for indoor visible light communication systems.) Platform: |
Size: 4096 |
Author:Mortimerr
|
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