FIR Filter Design with Kaiser Window

Filters play a major role in designing signal processing systems. Between analog filters and digital filters, digital filters are superior to the analog filters in many aspects. When designing, two types of digital filters can be observed based on their impulse response.

• FIR filters Finite extended Impulse Response
• IIR filters Infinite extended Impulse Response

There are two methods to design FIR digital filters,

• Windowing method
• Weighted Chebyshev method

Detailed descriptions of the two methods are available in [1]. Amongst these two methods, the windowing method is simpler than optimizing method. Windowing method is used in conjunction with the Fourier Transform. In this method, the infinite length of the Fourier Transformed transfer function is truncated using a window function. Text [1] includes several different window functions. Among all the window functions, Kaiser Window contains adjustable main lobe width and a ripple ratio, resulting high quality filter transfer function which fulfills all the specifications.

This report contains the manual design and implementation of the digital FIR band pass filter using the Kaiser Window method. Since parameter values such as main lobe width, transition bandwidth and ripple ratio can be adjusted in the Kaiser window, it provides a high quality filter which satisfies all the specification requirements and meets all the aspects of the FIR filters.

Click here to generate Kaiser Window manually using the MATLAB software without using in built functions.

Reference

1. A.Antoniou, Digital Signal Processing : Signals, Systems and Filters, McGraw-Hill,
2006.

Bluetooth 5 for IoT

Introduction

Different iteration of previous Bluetooth (such as Bluetooth 4.0, 4.1, 4.2) are slight improvements of their predecessors with respect to the pairing time and low energy modes etc. they dose not change the manner they were used. But with the Bluetooth 5, uses and the features of the bluetooth changed considerably. while retain the features of bluetooth classic, Bluetooth 5 increases the capabilities of Bluetooth Low Energy in a massive scale.

Features

Main features include in the Bluetooth 5 are given below and these features enable vast range of new possibilities in the sense of IoT applications and communications.

• High Data rate
• Long range
• Advertising extensions
• Increased broadcast capacity
• Improved co-existence

When consider the data rate of Bluetooth 5, it is twice faster than its predecessor Bluetooth 4.2 i.e. Bluetooth 5 can support up to 2Mpbs data rate at the physical layer while Bluetooth 4.2 can only support 1Mbps. With this high data rates, data can be send quickly resulting low power consumption also bluetooth facilitate reliable over the air connectivity. Bluetooth 5 can support four discrete data rates, 2Mbps, 1Mbps, 500kbps and 125kbps. While 2Mbps gives higher throughput, 125Mbps improves sensitivity and support larger range as discussed in the next paragraph.

Not only high data rates, but bluetooth 5 has quadruple longer range than bluetooth 4.2. Specifically, in indoor environments it can extend up to 40m and in outdoor it can extend up to 240m, enabling vast bluetooth mesh networks. With 40m indoor coverage it is enough to cover up a standard home. Therefore, this will enable the possibilities to smart homes, industry automation systems and many IoT applications.

Bluetooth 5 has introduced advertise extensions to reduce the channel occupancy and channel congestion. This will provide the capability to offload data from 3 advertise channel to another set of data channels for use broadcasting channels efficiently. By introducing advertise extensions, Bluetooth 5 has increased its broadcast capacity by eight times than Bluetooth 4.2. Bluetooth 5 contains 3 advertise channels for backward compatibility and then it include another 37 secondary advertise channels to broadcast more data.

Further, Bluetooth 5 can support Periodic Advertising which enables devices (specially beacons) to send out changing information periodically. Last but not least Bluetooth 5 has improved its co-existence with other technologies. 2.45GHz band is very crowded with several communication technologies. Newly introduced Channel Sequencing Algorithm will reduce the potential interferences on the Bluetooth 5 from the 2.45GHz band(Wi-Fi,other Bluetooth devices) , at the edge of 2.45GHz band and neighboring LTE band.

Comparison with other Bluetooth versions

New possibilities for IoT

Previously, IoT compatibility of Bluetooth was initiated with Bluetooth 4.2. Introduction of Bluetooth Low Energy established Bluetooth as a communication medium for low powered IoT devices. Bluetooth 5 takes this to a one step further by introducing advertisement extensions along with the much reduced power consumption. When consider the features provided by Bluetooth 5 it is obvious that this new version of Bluetooth is targeting the IoT applications.

Bluetooth 5 will make the interation between IoT and user simple and effortless due to its conectionless communication. User does not required to download a specific application or setup a pairing connection with beacons or any other IoT device. Bluetooth 5 facilitate IoT applications by reducing the power required for the long range communication. This reduction is carried out using two methods.

•  Decrease the data rate
•  Use a error correction methods

There fore the maximum range of 240m is archive by the IoT device with a 125Kbps data rate. This will not affect the functionality of a low power IoT device since they do not produce large information. In order to maintain the reliability when increasing the range, Bluetooth 5 has adopt the Forward error Correction based on Hamming window. When consider smart home applications, Bluetooth 5 supplies enough coverage for the whole home facilitating to each bluetooth enabled IoT devices to ”talk” to each other. Not only homes, but also Bluetooth 5 can support IoT applications including automation systems and security solutions with coverage of a whole building or locality.

Next interesting factor for IoT support from Bluetooth 5 is its broadcast capacity increment by eight times. This highly influence the Beacon technology since each beacon can convey more information than in Bluetooth 4.2. This will lead to conserving power and time from both end. Further, with newly added location and navigation functionality will allowed beacons and other location based IoT devices to send custom information to other Bluetooth enabled devices with out any additional setups.

Nevertheless, Bluetooth 5 is flexible. Developers can choose customized Bluetooth configurations according to their applications. This will allow to discover more ways to optimize the functionality and archive the maximum throughput possible for a IoT device.

Discussion

To summaries, Introducing Bluetooth 5 is an evolutionary step in both Bluetooth and IoT. With more speed, great coverage, high broadcasting capabilities, flexibility and improved co existance with other technologies, Bluetooth 5 facilitate IoT devices to grow rapidly and power efficiency. But the only drawback that can identified is that even though Bluetooth 5 is backward compatible, in order to experience all these benefits, respective IoT devices and other devices should include Bluetooth 5 compatible chip sets.

References

1. Henrik Snellman, Mikko Savolainen, Jere Knaappila, Pasi Rahikkala, ”Bluetooth 5 Refined for IoT”, Silicon Labs, 2017.
2. P. P. Ray and S. Agarwal, ”Bluetooth 5 and Internet of Things : Potential and Architecture”, 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), Paralakhemundi, 2016, pp. 1461-1465
3. http://www.rfwireless-world.com/Terminology/Bluetooth-5-vs-bluetooth-4-2.html
4. https://www.bluetooth.com/specifications/bluetooth-core-specification/bluetooth5

FPGA Based Processor Implementation

The goal of this project is to design an application specific CPU model which can use to perform image down sampling. Model build using Verilog language and simulated using iSim software. Actual hardware implementation was built on Field programmable gate array - FPGA (Spartan 6) and results were astonishing. Following report presents the methodology and results obtained using simulation and hardware model.

Click here for project report

Click here for source code

The difference between Sharp IR sensors and Ultrasonic sensors in object detection

 The basic difference between these two sensors is the medium that they use to sense the object. IR sensors use IR beams whereas ultrasonic sensors use ultrasonic beams instead. There are some external and internal factors that affect these results.

• External light

Since the sharp IR sensors have a weak light filtering system, the readings show a significant difference in bright day light and night.

As the counterpart, ultra sonic sensor uses a sonic burst which is not affected by the light conditions. So the reading stays as same for bright day light and night.

• Color of the surface

As a fact we know that black surfaces absorb light and white surfaces reflect light, the same principle is applicable for the sharp IR sensors. White surfaces reflect the IR beam and black surfaces absorb most of the energy of the incident beam. Therefore, white surfaces show almost accurate readings for a wider range of distances than the black surfaces, where the accuracy persists only up to a few centimeters.

Since different colored surfaces cannot absorb ultrasonic beam differently, readings stay same for every colored surfaces.

• Size of the beam

                  Sharp IR beam angle is limited to 10 degrees and ultrasonic sensor has a 60-degree beam.        

Therefore, sharp IR sensor can exactly locate the position of the object whereas ultrasonic sensor cannot locate the exact position of the object. But, it is better for sensing obstacles due to the wide range.

• Nature of the surface

If objects have rough surfaces, they can scatter the incident beam emitted by both the sensors.

• Inclined objects

If the object is not perpendicular to the ground, then again readings will be off according to the inclination.

• External sound

If you are using ultrasonic sensor for a robot, then motors are producing humming noises which will interfere with ultrasonic bursts produced by the sensor. Also, surrounding noises will affect the readings.

When using more than one ultrasonic sensor, sound bursts from a one sensor may be identified by another sensor as its own, due to its wider beam. This will not course much effect on the sharp IR sensor because of its narrower beam.