Skip to content Skip to navigation

Connexions

You are here: Home » Content » Detection of Signals Transmitted over Complicated Channels

Navigation

Recently Viewed

This feature requires Javascript to be enabled.

Detection of Signals Transmitted over Complicated Channels

Module by: Don Johnson. E-mail the author

User rating (How does the rating system work?)
Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

:
(0 ratings)

Note: Your browser may not currently support MathML. See our browser support page for additional details. You can always view the correct math in the PDF version.

In considering the additive, white Gaussian noise channel, we found that the performance of the optimum receiver depended only on the signal-to-noise ratio. Consequently, details of the signal waveforms do not matter to a great degree: Energy is what counts. We continue with the study of channels which corrupt the transmitted signal in different and more complicated (from a theoretical viewpoint) ways. We shall see that signal waveforms do matter. Consequently, the design of signal sets become more involved.

Dispersive Channels

We first consider the corruption of the transmitted signal by a linear filter.

Figure 1
Figure 1 (dispersive.png)
Such channels are said to be dispersive channels. h CH tτ h CH t τ denotes the impulse response of the deterministic, possibly time-varying, linear filter. s i * t=0T h CH tτ s i τdτ s i * t τ 0 T h CH t τ s i τ As far as the receiver is concerned, the transmitter is using the signal set s i * t s i * t . Consequently, the solution of the optimum receiver is straightforward using the theory as it stands. However, a complication arises in the detailed consideration of these signals' durations. The channel tends to increase the duration of s i t s i t , hence the origin of the term dispersive. We first consider the problem where a sufficient amount of time is allowed for the transmission of a "bit" so that successive transmissions do not overlap each other.

Content actions

Give Feedback:

E-mail the module author | Rate module ( How does the rating system work?)

Rating system

Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

(0 ratings)

Download:

Add module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections directly in Connexions. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need a Connexions account to use 'My Favorites'.

| A lens (?)

Definition of a lens

Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual Connexions member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks