Tuesday, 9 January 2018
DTMF Based Project
Dual-tone multi-frequency signaling DTMF Based Project using M8870 IC
By Yasir Iqbal
DESCRIPTION
In this project, which based on DTMF decoder Ic M8870, we showing the output of M8870 ic in 7 segment. The 4 bit data output of M8870 ic further connected with LS7447 decoder which is BCD decoder to 7 segment display unit.
Input tone from mobile gives to M8870 ic which further connected to BCD decoder LS7447 ic and then 7 segment.
When we press any key from mobile (mobile keypad tone should be on) the tone goes to decoder ic which receiver certain key frequency and then converts to 4 bit data which further given to BCD decoder and then 7 segment connected to BCD decoder show that number which key pressed on mobile.
It can remotely operate when someone calls to that mobile (which is connected to circuit) and remotely press any dial number which can be received and circuit can show dial pressed number of caller .
Circuit Diagram
Components required
- DTMF decoder IC (M-8870) 5. BCD decoder 7447
- Resistors (100kΩ; 70kΩ; 390kΩ;470Ω) 6. 7 Segment
- Capacitors (0.1µFx 2)
- Crystal oscillator (3.579545MHz)
Table showing DTMF Low and High frequency tones and decoded output
Uses of other pins:
- The entire process from frequency detection to latching of the data, is controlled by steering control circuit consisting of St/GT, Est pins, resistor (390kΩ) and a capacitor (0.1µF).
- 5th Pin, INH is an active high pin, inhibits detection of A, B, C, D tones of character.
- 6th Pin, PWDN is an (active high), inhibits the working of oscillator thus stops the working of our circuit.
- The 10th pin 10; TOE is the output enable pin which is active high logic and enables the latching of the data on the data pins Q0, Q1, Q2, and Q3.
- 15th Pin StD is the Data valid pin, turn out to be high on detection of valid DTMF tone or else it remains low.
- Pins 7 (OS1) and 8 (OS2) are used to connect crystal oscillator. An oscillator of frequency 3.579545 MHz is used here.
An Experimental Realization of Spectrum Sensing in Cognitive Radio.
An Experimental Realization of Spectrum Sensing in Cognitive Radio.
Presentation In Model Form.
The purpose of this project is to effectively utilize the bandwidth. The implementation of Cognitive radio makes sure full use of spectrum for secondary user while primary user (licensed user) is not available. Spectrum sensing is the function of cognitive radio which responsible to sense and understand its spectrum environment then detect unused spectrum in licensed band. The research paper on this project has been published in 2nd International Electrical Engineering Conference IEEC 2017 here.
Proposed Work
We have
implemented an essential part of cognitive radio which is termed as spectrum
sensing. As described above the spectrum sensing is a technique by which we
determine which part of the licensed user spectrum is available. This spectrum
sensing technique has many algorithms such as ED, MFD and FD. We have
implemented ED (energy detection).
For this purpose
the platform used are MATLAB and raspberry pi. The MATLAB is used as a PU or
licensed user and raspberry pi act as SU or unlicensed user.
In this scenario
the PU has five channels. On these five channels, MATLAB randomly allocate the
user and starts transmission. This can be shown in the figure below.
Fig ure 6.1: PU Transmission
It is clear from
the above figure that out of 5 channels the 1st, 4th and 5th channels are allocated to
PU. Now the MATLAB transmits the signal to raspberry pi. The raspberry pi and
MATLAB are connected via Ethernet cable.
Raspberry pi
which is our sensor after receiving the signal performs FFT. After performing
FFT the energy is calculated. The calculated energy is then compared with the
predefined threshold. The threshold can be static and it could be variable
depending upon the selection.
If the value of
energy of the channel is less than the threshold then PU is not present else it
is present. The channels which are not used by the PU are called spectrum
holes. As shown in the figure 6.1.
Figure 6.2: Indicating Spectrum holes And PU
The SU (Raspberry pi) starts
transmission on the Spectrum holes. This can be shown in figure 6.2.
Figure 6.3: SU Transmission on
Spectrum Holes
Process
·
Generate Channels Randomly: We generated five
channels on different frequencies and set a center frequency for each channel.
As we are not working on real spectrum, we have generated channels of our own
through MATLAB.
·
Sensing: Spectrum is sensed by Raspberry Pi and
PSD/ energy of each channel is calculated in this step by calculating the
energy and summing it up.
·
Threshold: we have set a fixed threshold, on
calculating energy of channels it has been comparing to a threshold.
·
Decision: If the calculated energy is less than
the threshold it detects that PU is absent and if the calculated energy is
greater than threshold it detects that the PU is present.
·
Allocation: On detecting which of the channels
are vacant, Raspberry Pi allocates those channels to a secondary user which can
use the channel until PU resumes its transmission.
Results And Simulation
The results we
have after using algorithm of energy detection and coding on Raspberry Pi are
shown as follows.
We run the
algorithm of energy detection on Raspberry pi and show the results through
graphs and on circuit through LEDs.
Figure 6.4: MATLAB results (a)
The above graph
shows the detection of primary user. On x-axis frequencies are mentioned and on
y-axis mentioned power. In above graph, channel 1st, 3rd and channel 5th
indicate the presence of signal whereas the other three channels are vacant
indicating the spectrum holes.
Figure 6.5: MATLAB results (b)
This graph shows
that the spectrum holes are now in use by secondary user. In figure. we
received no primary user on channel-2 and channel-4, after sensing one out of
these two channels are allocated to secondary user for transmission.
Presentation In Model Form.
Subscribe to:
Posts (Atom)