30-05-2013, 04:05 PM
MSP430 and nRF24L01 based Wireless Sensor Network Design with
Adaptive Power Control
[attachment=54531]
Abstract
In this paper, we have developed a Low cost and low
power Wireless Sensor Networks (WSNs) Node
using MSP430 and Nordic nRF24L01. The
architectural and circuit details are presented. This
architecture fulfils the requirements of low power,
compact size and self-organization with a new feature
of adaptive Power Control. For Low power
consumption Adaptive Power control technique is
used. In this technique we can vary the transmitted
power according to the distance between the nodes,
which is also the different feature of this WSN.
Adaptive power algorithm that uses both RF output
Power and Transmission rate to be adjusted according
to the distance between the Nodes which will
maximize the battery life time. All the Radio modules
available in the market are utilizing constant power
transmission during its operation. Hence significant
reduction in energy consumption is possible based on
the proposed approach which prolongs the battery
lifetime.
Introduction
A wireless sensor network is a network made up of
hundreds or thousands of Sensor nodes, which are
densely deployed in an unattended environment.
These nodes are capable of communicating by means
of wireless communications, sensing and selfcomputation
(software, hardware, algorithms) [1].
Hence the wireless sensor network is the result of the
combination of sensor, embedded techniques,
distributed information processing, and
communication mechanisms. The sensor network is
more application specific than traditional networks
designed to accommodate various applications.
Hardware details of WSN Node
The hardware consists of MSP430 connected with
nRF24L01 as shown in Figure1.
MSP430F1612
The Texas Instruments MSP430 family of ultra low
power microcontroller consists of several devices
featuring different sets of peripherals targeted for
various applications. The architecture, combined with
five low power modes is optimized to achieve
extended battery life in portable measurement
applications. The device features a powerful 16-bit
RISC CPU, 16-bit registers, and constant generators
that attribute to maximum code efficiency [3].
NORDIC nRF24L01:
The nRF24L01 is a single chip radio transceiver for
the global, license-free 2.4 GHz ISM band. The low
cost nRF24L01 is designed to merge very high speed
communications (up to 2Mbit/s) with extremely low
power (the RX current is just 12.5mA) [4]. The
transceiver consists of a fully integrated frequency
synthesizer, a power amplifier, crystal oscillator,
demodulator, modulator and Enhanced ShockBurst
protocol engine. In addition, the nRF24L01 also
offers an innovative on-chip hardware solution called
‘MultiCeiver’ that can support up to six
simultaneously communicating wireless devices. This
makes it ideal for building wireless Personal Area
Networks in a wide range of applications. The PCB
of this WSN node is circular, having two inches
diameter.
Adaptive Power Control Algorithm
Power efficiency is very important in wireless sensor
networks because the sensors typically run on
batteries and long lifetime is highly desirable. The
algorithm used here is to set the transmission strength
of the route update message. By setting the
transmission strength, nodes can store the RSS
(Received Signal Strength) and with the known
transmission setting, distance to the transmitter can
be estimated the node. Based on the estimated
distance the node will then adjust its transmission
power. Variable Transmission Control sets the
transmission power based specifically on the RSS. It
has multiple limits with each being associated with a
different transmission setting.
Experimental results:-
The WSN nodes are arranged in the network as
shown in Figure 3 where N1, N2, N3, N4, N5, N6 are
the different Nodes. ‘S’ indicates the destination node
which is connected to computer. The data from the
network is processed and displayed by this computer.
The Node lifetime depends upon the power
consumption of MSP430, transmit and receive mode
consumption of nRF24L01. Also it depends upon the
sleep and active times i.e. duty cycle [7,8]. The node
is programmed with <1% of duty cycle [9]. The
Average current consumption and the node lifetime
are calculated by taking the different parameters as
shown in Table 4.
Conclusion
We have designed a very compact node with
maximum possible power efficiency. The node has
many ports available for future expansion of the
nodes. The Power management occurs as Low duty
cycle is considered. We have developed our own
protocol stack efficient than Zigbee with simple
programming compilers like cross studio.
The adaptive algorithm saves the power to a great
extent as at high power level transmission due to
high data rate the transmission will be faster
causing the node ON time to be reduced. The
transmission time is almost half than required by 1
Mbps rate. Hence the battery life can be further
increased.
Adaptive Power Control
[attachment=54531]
Abstract
In this paper, we have developed a Low cost and low
power Wireless Sensor Networks (WSNs) Node
using MSP430 and Nordic nRF24L01. The
architectural and circuit details are presented. This
architecture fulfils the requirements of low power,
compact size and self-organization with a new feature
of adaptive Power Control. For Low power
consumption Adaptive Power control technique is
used. In this technique we can vary the transmitted
power according to the distance between the nodes,
which is also the different feature of this WSN.
Adaptive power algorithm that uses both RF output
Power and Transmission rate to be adjusted according
to the distance between the Nodes which will
maximize the battery life time. All the Radio modules
available in the market are utilizing constant power
transmission during its operation. Hence significant
reduction in energy consumption is possible based on
the proposed approach which prolongs the battery
lifetime.
Introduction
A wireless sensor network is a network made up of
hundreds or thousands of Sensor nodes, which are
densely deployed in an unattended environment.
These nodes are capable of communicating by means
of wireless communications, sensing and selfcomputation
(software, hardware, algorithms) [1].
Hence the wireless sensor network is the result of the
combination of sensor, embedded techniques,
distributed information processing, and
communication mechanisms. The sensor network is
more application specific than traditional networks
designed to accommodate various applications.
Hardware details of WSN Node
The hardware consists of MSP430 connected with
nRF24L01 as shown in Figure1.
MSP430F1612
The Texas Instruments MSP430 family of ultra low
power microcontroller consists of several devices
featuring different sets of peripherals targeted for
various applications. The architecture, combined with
five low power modes is optimized to achieve
extended battery life in portable measurement
applications. The device features a powerful 16-bit
RISC CPU, 16-bit registers, and constant generators
that attribute to maximum code efficiency [3].
NORDIC nRF24L01:
The nRF24L01 is a single chip radio transceiver for
the global, license-free 2.4 GHz ISM band. The low
cost nRF24L01 is designed to merge very high speed
communications (up to 2Mbit/s) with extremely low
power (the RX current is just 12.5mA) [4]. The
transceiver consists of a fully integrated frequency
synthesizer, a power amplifier, crystal oscillator,
demodulator, modulator and Enhanced ShockBurst
protocol engine. In addition, the nRF24L01 also
offers an innovative on-chip hardware solution called
‘MultiCeiver’ that can support up to six
simultaneously communicating wireless devices. This
makes it ideal for building wireless Personal Area
Networks in a wide range of applications. The PCB
of this WSN node is circular, having two inches
diameter.
Adaptive Power Control Algorithm
Power efficiency is very important in wireless sensor
networks because the sensors typically run on
batteries and long lifetime is highly desirable. The
algorithm used here is to set the transmission strength
of the route update message. By setting the
transmission strength, nodes can store the RSS
(Received Signal Strength) and with the known
transmission setting, distance to the transmitter can
be estimated the node. Based on the estimated
distance the node will then adjust its transmission
power. Variable Transmission Control sets the
transmission power based specifically on the RSS. It
has multiple limits with each being associated with a
different transmission setting.
Experimental results:-
The WSN nodes are arranged in the network as
shown in Figure 3 where N1, N2, N3, N4, N5, N6 are
the different Nodes. ‘S’ indicates the destination node
which is connected to computer. The data from the
network is processed and displayed by this computer.
The Node lifetime depends upon the power
consumption of MSP430, transmit and receive mode
consumption of nRF24L01. Also it depends upon the
sleep and active times i.e. duty cycle [7,8]. The node
is programmed with <1% of duty cycle [9]. The
Average current consumption and the node lifetime
are calculated by taking the different parameters as
shown in Table 4.
Conclusion
We have designed a very compact node with
maximum possible power efficiency. The node has
many ports available for future expansion of the
nodes. The Power management occurs as Low duty
cycle is considered. We have developed our own
protocol stack efficient than Zigbee with simple
programming compilers like cross studio.
The adaptive algorithm saves the power to a great
extent as at high power level transmission due to
high data rate the transmission will be faster
causing the node ON time to be reduced. The
transmission time is almost half than required by 1
Mbps rate. Hence the battery life can be further
increased.