mkhan
Full Member level 3
mimo channel non zero mean
Hi,
I think the most important and difficult part in any wireless communication system is to deal with wireless channel. Therefore, I think i shoud discuss some issues in wireless channel here.
The first important point is to model the wireless channel. As we know that wireless channel is non stationary and randomly varying over time. But in general the factors on which channel variation depends are carrier frequency and mobility of user and environment. In order to model the channel, each channel vector can be modeled as a Complex Gaussian distributed random variable with mean µ and variance σ. These channel vectors are independent from each other.
Wireless channel changes randomly over time as i mentioned earlier, but we assume that for a certian period of time, the channel remains constant. We call that short period of time as Block and thats why we assume that wirelss channel is Block stationary, i.e. it is static during each block but changing from block to block. This is known as Block fadig as well. If the channel has zero mean i.e. µ = 0 the channel model is referred as Rayleigh and if it is not zero then the model is known as Ricean. This is because when mean is zero, channel distribution is similar to the Rayleigh distribution and when it is non-zero the channel distribution is similar to Ricean distribution. Usually Ricean fading model is used when there is a line of sight scenerio in the communication system.
In MATLAB we can model this wireless channel as:
randn('state',0);
randn('state',0);
h = complex(normrnd(0,sqrt(0.5),NU*NR,NT),normrnd(0,sqrt(0.5),NU*NR,NT));
Here this channel model is with zero mean, unit variance, NU*NR \times NT .
There are some important issues in channel state information (CSI), channel distribution information (CDI) at the receiver and transmitter.
Also another important and open area of research is how to fed back this information from MS to BS (I am talking about BC channel i.e. downlink) accurately. There is an issue of delay in it, that is when this channel information reaches at BS it might be outdated for the BS, or it might be altered during the transmision from MS to BS.
I know there is lot more to discuss about wireless channel. This is just my humble effort to give an overview of the importance of wireless channel. I appreciate any comments, any changes, any errors in this regard in order to increase our understanding of this important aspect of wireless communication.
Regards,
MAK.
Ref: 1. Introduction to space time wirelss communication by A. Paulraj et al. Cambridge University Press, 2003.
2. Fundamentals of wirelss communications by David Tse and P. Viswanath, Cambridge University Press, 2005.
And many more books, papers, and thesis which i benefit over the time, but its very long list of references to mention. But I do acknowledge their work from which I learnt a lot and still learning.
Hi,
I think the most important and difficult part in any wireless communication system is to deal with wireless channel. Therefore, I think i shoud discuss some issues in wireless channel here.
The first important point is to model the wireless channel. As we know that wireless channel is non stationary and randomly varying over time. But in general the factors on which channel variation depends are carrier frequency and mobility of user and environment. In order to model the channel, each channel vector can be modeled as a Complex Gaussian distributed random variable with mean µ and variance σ. These channel vectors are independent from each other.
Wireless channel changes randomly over time as i mentioned earlier, but we assume that for a certian period of time, the channel remains constant. We call that short period of time as Block and thats why we assume that wirelss channel is Block stationary, i.e. it is static during each block but changing from block to block. This is known as Block fadig as well. If the channel has zero mean i.e. µ = 0 the channel model is referred as Rayleigh and if it is not zero then the model is known as Ricean. This is because when mean is zero, channel distribution is similar to the Rayleigh distribution and when it is non-zero the channel distribution is similar to Ricean distribution. Usually Ricean fading model is used when there is a line of sight scenerio in the communication system.
In MATLAB we can model this wireless channel as:
randn('state',0);
randn('state',0);
h = complex(normrnd(0,sqrt(0.5),NU*NR,NT),normrnd(0,sqrt(0.5),NU*NR,NT));
Here this channel model is with zero mean, unit variance, NU*NR \times NT .
There are some important issues in channel state information (CSI), channel distribution information (CDI) at the receiver and transmitter.
Also another important and open area of research is how to fed back this information from MS to BS (I am talking about BC channel i.e. downlink) accurately. There is an issue of delay in it, that is when this channel information reaches at BS it might be outdated for the BS, or it might be altered during the transmision from MS to BS.
I know there is lot more to discuss about wireless channel. This is just my humble effort to give an overview of the importance of wireless channel. I appreciate any comments, any changes, any errors in this regard in order to increase our understanding of this important aspect of wireless communication.
Regards,
MAK.
Ref: 1. Introduction to space time wirelss communication by A. Paulraj et al. Cambridge University Press, 2003.
2. Fundamentals of wirelss communications by David Tse and P. Viswanath, Cambridge University Press, 2005.
And many more books, papers, and thesis which i benefit over the time, but its very long list of references to mention. But I do acknowledge their work from which I learnt a lot and still learning.
