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OFDMchannelestimate
- 书文提出了一种称为平均反馈(AF)的新算法．该算法利用两个相邻的 0FDM符号之间的荧联信息对LS算法的估计结果进行平均和反馈．以减少离斯白噪声岛子信道间干扰(1cI)对信道估计结 果的影囔。-The book article proposed one kind is called the average to feed back (AF) the new algorithm. This algorithm uses two neighboring between the 0FDM ma
On-the-Role-of-Estimate-and-Forward-With-Time
- In this paper, we focus on the general relay channel. We investigate the application of the estimate-and-forward (EAF) relaying scheme to different scenarios. Specifically, we study assignments of the auxiliary random variable that always satis
Diversity-techniques-for-blind-channel-equalizati
- Diversity techniques for blind channel equalization in mobile communications.This paper deals with blind equalization of mobile channels, which are either frequency-selective or multiplicative. The proposed algorithm can be used for channel dis
comm
- 构建了简单的通信系统，其间对载波相位进行了估计，同时在函数中给出了估计误差，还计算了误码率以及采用信道编码的误码率-Construction of a simple communication system, during which the estimate of the carrier phase, and gives in function of the estimation error, also calculated BER and the channel coding error r
HW4
- A 16-QAM signal X, whose power is normalized as unity, is transmitted with OFDM over the discrete-time channel model h which has been used in Homework #2 and #3. As depicted in the below figure, the transmitter (TX) is now equipped with an N-point ID
Channel-Estimation-for-DBLAST-OFDM-Systems
- 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 fr
channel_estimation_OFDM
- this program explane how estimate th radio channel using OFDM
07393877
- Signal identification represents the task of a receiver to identify the signal type and its parameters, with applications to both military and commercial communications. In this paper, we investigate the identification of spatial multiplexing (
Feature-Denoising
- joint sparse representation (JSR)方法用于车内语音增强的特征降噪算法-address reducing the mismatch between training and testing conditions for hands-free in-car speech recognition. It is well known that the distortions caused by background noise, channel effec