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problem of blind demodulation of multiuser
information symbols in a high-rate code-division multiple-access
(CDMA) network in the presence of both multiple-access interference
(MAI) and intersymbol interference (ISI) is considered.
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we investigate a new blind adaptive fractionally-spaced TEQ (FS-TEQ) for multicarrier systems in order to reduce efficiently intersymbol interference. We also exploit the cyclic prefix and fractionally-spaced TEQ to create a blind adaptive globally c
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we investigate a new blind adaptive fractionally-spaced TEQ (FS-TEQ) for multicarrier systems in order to reduce efficiently intersymbol interference. We also exploit the cyclic prefix and fractionally-spaced TEQ to create a blind adaptive globally c
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we investigate a new blind adaptive fractionally-spaced TEQ (FS-TEQ) for multicarrier systems in order to reduce efficiently intersymbol interference. We also exploit the cyclic prefix and fractionally-spaced TEQ to create a blind adaptive globally c
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we investigate a new blind adaptive fractionally-spaced TEQ (FS-TEQ) for multicarrier systems in order to reduce efficiently intersymbol interference. We also exploit the cyclic prefix and fractionally-spaced TEQ to create a blind adaptive globally c
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we investigate a new blind adaptive fractionally-spaced TEQ (FS-TEQ) for multicarrier systems in order to reduce efficiently intersymbol interference. We also exploit the cyclic prefix and fractionally-spaced TEQ to create a blind adaptive globally c
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使用LMS算法进行盲多用户检测，并计算出信干比和误码率-LMS algorithm using the blind multi-user detection, and calculate the signal to interference ratio and bit error rate
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只使用待测用户的观测数据，不需要其他用户（干扰用户）信息就可以抵消多址干扰进行检测的自适应检测器称为盲自适应多用户检测器，常简称为盲多用户检测。用LMS算法更新检测器系数时即为盲自适应多用户检测的LMS算法-Use only tested the user' s observations, no other user (interference user) information to be offset by multiple access interference detection
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只使用待测用户的观测数据，不需要其他用户（干扰用户）信息就可以抵消多址干扰进行检测的自适应检测器称为盲自适应多用户检测器，常简称为盲多用户检测。用RLS算法跟新检测器系数时即为盲自适应多用户检测的RLS算法，-Use only tested the user' s observations, no other user (interference user) information to be offset by multiple access interference detection
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仿真了盲辨识RLS和LMS算法的时间平均信干比，分析了两者的多址干扰抑制能力-Simulation of the blind identification algorithm RLS and LMS average signal to interference ratio of the two algorithms of multi-access interference suppression
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一种改进的适于慢衰落信道的恒模盲均衡算法 CDMA系统盲自适应干扰抑制 -An improved fit for slow fading channel constant modulus blind equalization algorithm Adaptive Interference Suppression for CDMA Systems
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自适应均衡器设计用于抑制信号失真，自适应均衡器节拍系数是时变调整的。-Adaptive equalizers remove signal distortion attributed to intersymbol interference in band-limited
channels. The tap coefficients of adaptive equalizers are time-varying and can be adapted using
several methods
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两种算法（LMS和RLS）实现CDMA系统盲多用户检测的仿真。结论验证了在加性高斯白招生信道下、同步DS-CDMA系统中接收机应用这两种盲多用户检测算法抑制多址干扰（MAI: multiple access interference）和码间串扰（ISI: inter symbol interference）的能力,仿真实验与理论推导相吻合。实验与理论都表明,RLS性能好于LMS，而LMS计算量明显小于RLS。-This paper discusses two algorithms (LMS an
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Adaptive equalization教程-Adaptive equalizers compensate for signal distortion
attributed to intersymbol interference (ISI), which is
caused by multipath within time-dispersive channels.
Typically employed in high-speed communication
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An Adaptive Block-Based Eigenvector Equalization for Time-Varying Multipath Fading Channels.In this paper we present an adaptive Block-
Based EigenVector Algorithm (BBEVA) for blind equalization
of time-varying multipath fading channels. In addit
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Blind Interference Alignment
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In this paper, we investigate blind channel estimation for Multiple Input Multiple Output (MIMO) multi-carrier
CDMA (MC-CDMA) systems in the uplink scenario. An Autocorrelation Contribution Matrix (ACM) method is proposed in
comparison with the sub
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盲干扰对齐(Blind Interference Alignment,简称BIA)是一种改良于干扰对齐算法的基于MIMO技术下的干扰抑制算法,(Blind Interference Alignment With Diversity)
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盲干扰对齐(Blind Interference Alignment,简称BIA)是一种改良于干扰对齐算法的基于MIMO技术下的干扰抑制算法(Blind Interference Alignment)
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干扰对齐是一种有效的干扰管理机制，通过预编码技术使干扰在接收端重叠在一起，以彻底消除干扰对期望信号的影响与忽略干扰、解码/消除干扰以及正交接入（避免干扰）等现有处理干扰的方法不同，IA通过压缩干扰所占的信号维度，使系统获得最大自由度(Interference Alignment (IA))
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