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Zigbee baseband hardware modeling for Internet of Things IEEE 802.15.4 compliance
Adiono T.a, Rahayu R.M.a
a Microelectronics Center, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2017 IEEE.This paper is modeling the hardware for baseband communication in Internet of things (IoT) Chip with processor 32 bit RISCx. Based on IEEE 802.15.4 about Wireless Personal Area Networks (WPANs), for zigbee with frequency 2450 MHz we have to used Direct Sequence Spreading Spectrum (DSSS) and for the communication modulation we have to used Offset Quadrature Phase Shift Keying (O-QPSK). In this hardware modeling we used the AWGN (Additive White Gaussian Noise) and Rayleigh fading as part of non ideal system in the channel. In receiver we used costas loop to recover the carrier. as it is a hardware modeling, we compare Bit Error Rate (BER) between 6 bit and 8 bit. There is a big BER difference between the 6 bit system and the 8 bit system. 8 bit system has a better bit error rate but the chip area that it used is bigger. Contrary for the 6 bit, the chip area used is smaller but the bit error rate is worse than the 8 bit.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Additive White Gaussian noise,AWGN,Communication modulations,Direct sequence spreading,DSSS,OQPSK,Wireless personal area networks,WPANs[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]AWGN,DSSS,OQPSK,WPANs,Zigbee[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICEEI.2017.8312420[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]