DFT-S OFDM system uplink multiple access block diagram, subcarrier allocation method could be used with IFDMA. Through the carrier allocation scheme, the user allocated sub-carriers do not overlap each other, and thus are not affected by the superimposed disturbance of each users signal. Suppose now that the multiuser signal can be separated using a carrier signal mapping method. The introduction of instantaneous carrier frequency offset can be considered the same, as the normalized relative frequency shift factor is equal.
- Area and Power Consumption is High
- Noise based signal
In the proposed system we are replace the transmission channel of RF to Optical technology. The proposed work block diagram is shown in below figure. In this block diagram consists of M- point DFT and IDFT transform, N- point DFT and IDFT transform, cyclic prefix technique, DAC, ADC and Optical transceiver.
Discrete Fourier transform
In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into an equivalent-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies. It has the same sample-values as the original input sequence. The DFT is therefore said to be a frequency domain representation of the original input sequence. If the original sequence spans all the non-zero values of a function, its DTFT is continuous (and periodic), and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic function, the DFT provides all the non-zero values of one DTFT cycle.
The DFT is the most important discrete transform, used to perform Fourier analysis in many practical applications. In digital signal processing, the function is any quantity or signal that varies over time, such as the pressure of a sound wave, a radio signal, or daily temperature readings, sampled over a finite time interval (often defined by a window function). In image processing, the samples can be the values of pixels along a row or column of a raster image. The DFT is also used to efficiently solve partial differential equations, and to perform other operations such as convolutions or multiplying large integers.
Since it deals with a finite amount of data, it can be implemented in computers by numerical algorithms or even dedicated hardware. These implementations usually employ efficient fast Fourier transform (FFT) algorithms; so much so that the terms “FFT” and “DFT” are often used interchangeably. Prior to its current usage, the “FFT” initialise may have also been used for the ambiguous term “finite Fourier transform”.
The Inverse Discrete Fourier Transform (IDFT)
The Fourier transform takes a signal in the so called time domain (where each sample in the signal is associated with a time) and maps it, without loss of information, into the frequency domain. The frequency domain representation is exactly the same signal, in a different form. The inverse Fourier transform maps the signal back from the frequency domain into the time domain.
A time domain signal will usually consist of a set of real values, where each value has an associated time (e.g., the signal consists of a time series). The Fourier transform maps the time series into a frequency domain series, where each value is a complex number that is associated with a given frequency. The inverse Fourier transform takes the frequency series of complex values and maps them back into the original time series. Assuming that the original time series consisted of real values, the result of the IDFT will be complex numbers where the imaginary part is zero.
Let us consider one subcarrier (subcarrier +1 specified in IEEE 802.11a specification) alone. In the figure shown below, the blue line corresponds to the original sinusoidal where one cycle of the sinusoidal is of duration 64 samples ( with 20MHz sampling), corresponding to subcarrier of frequency 312.5kHz.
Optical communication, also known as optical telecommunication, is communication at a distance using light to carry information. It can be performed visually or by using electronic devices. The earliest basic forms of optical communication date back several millennia, while the earliest electrical device created to do so was the photophone, invented in 1880.
An optical communication system uses a transmitter, which encodes a message into an optical signal, a channel, which carries the signal to its destination, and a receiver, which reproduces the message from the received optical signal. When electronic equipment is not employed the ‘receiver’ is a person visually observing and interpreting a signal, which may be either simple (such as the presence of a beacon fire) or complex (such as lights using color codes or flashed in a Morse code sequence).
Free-space optical communication has been deployed in space, while terrestrial forms are naturally limited by geography, weather and the availability of light. This article provides a basic introduction to different forms of optical communication.
Basic function of optical communication:
For gigabits and beyond gigabits transmission of data, the fiber optic communication is the ideal choice. This type of communication is used to transmit voice, video, telemetry and data over long distances and local area networks or computer networks. A fiber Optic Communication System uses light wave technology to transmit the data over a fiber by changing electronic signals into light.
Some exceptional characteristic features of this type of communication system like large bandwidth, smaller diameter, light weight, long distance signal transmission, low attenuation, transmission security, and so on make this communication a major building block in any telecommunication infrastructure. The subsequent information on fiber optic communication system highlights its characteristic features, basic elements and other details.
Unlike copper wire based transmission where the transmission entirely depends on electrical signals passing through the cable, the fiber optics transmission involves transmission of signals in the form of light from one point to the other. Furthermore, a fiber optic communication network consists of transmitting and receiving circuitry, a light source and detector devices like the ones shown in the figure.
When the input data, in the form of electrical signals, is given to the transmitter circuitry, it converts them into light signal with the help of a light source. This source is of LED whose amplitude, frequency and phases must remain stable and free from fluctuation in order to have efficient transmission. The light beam from the source is carried by a fiber optic cable to the destination circuitry wherein the information is transmitted back to the electrical signal by a receiver circuit.
Basic Elements of a Fiber Optic Communication System:
There are three main basic elements of fiber optic communication system. They are
- Compact Light Source
- Low loss Optical Fiber
- Photo Detector
Accessories like connectors, switches, couplers, multiplexing devices, amplifiers and splices are also essential elements in this communication system.
Compact Light Source:
Depending on the applications like local area networks and the long haul communication systems, the light source requirements vary. The requirements of the sources include power, speed, spectral line width, noise, ruggedness, cost, temperature, and so on. Two components are used as light sources: light emitting diodes (LED’s) and laser diodes.
Laser diode structure
The light emitting diodes are used for short distances and low data rate applications due to their low bandwidth and power capabilities. Two such LEDs structures include Surface and Edge Emitting Systems. The surface emitting diodes are simple in design and are reliable, but due to its broader line width and modulation frequency limitation edge emitting diode are mostly used. Edge emitting diodes have high power and narrower line width capabilities.
For longer distances and high data rate transmission, Laser Diodes are preferred due to its high power, high speed and narrower spectral line width characteristics. But these are inherently non-linear and more sensitive to temperature variations.
LED vs Laser
Nowadays many improvements and advancements have made these sources more reliable. A few of such comparisons of these two sources are given below. Both these sources are modulated using either direct or external modulation techniques.
- Increases the speed of Data transmission, and reduces the noise.
- Reduced the area, delay and power.