Adaptive subcarrier modulation for indoor public safety body-to-body networks

Abstract

In this contribution, we present the Bit Error Rate characteristics for an indoor, wideband body-to-body channel between two firefighters when using IEEE 802.11 ac, which is proven a very suitable standard for future, wideband public safety networks. Moreover, the BER and throughput charac-teristics, when applying both transmission blocking, fixed and adaptive, subcarrier modulation are presented. These charac-teristics show an increased throughput when applying adaptive subcarrier modulation. We have conducted a wideband, indoor channel sounder campaign at 3.6 GHz with 120 MHz useful bandwidth, simulating real-life rescue operations performed by two simultaneously moving members of the Rapid Intervention Team. Both firefighters were equipped with low-profile, light-weight and energy-efficient Ultra Wideband Cavity-Backed slot antennas in Substrate Integrated Waveguide technology, unobtru-sively deployed inside the front and back sections of their jackets, providing 2 × 2 MIMO c... Abstract-In this contribution, we present the Bit Error Rate characteristics for an indoor, wideband body-to-body channel between two firefighters when using IEEE 802.11 ac, which is proven a very suitable standard for future, wideband public safety networks. Moreover, the BER and throughput characteristics, when applying both transmission blocking, fixed and adaptive, subcarrier modulation are presented. These characteristics show an increased throughput when applying adaptive subcarrier modulation. We have conducted a wideband, indoor channel sounder campaign at 3.6 GHz with 120 MHz useful bandwidth, simulating real-life rescue operations performed by two simultaneously moving members of the Rapid Intervention Team. Both firefighters were equipped with low-profile, lightweight and energy-efficient Ultra Wideband Cavity-Backed slot antennas in Substrate Integrated Waveguide technology, unobtrusively deployed inside the front and back sections of their jackets, providing 2 × 2 MIMO capability.

Comparative Analysis of Optical Multicarrier Modulations: An Insight into Machine Learning-based Multicarrier Modulation

“…In estimating the performance of the VLC-based multicarrier schemes, their performance relative to selected quadrature amplitude modulation (QAM) constellations for broadband application is adopted. The validated constellations are 4QAM, 16QAM, 64QAM and 256QAM respectively [21] which were evaluated in relation to the multicarrier schemes for a threshold bit error rate of 10 −4 and a total number of N=1024 subcarriers. To further improve on the modulation schemes' BER response, Artificial Neural network (ANN) was adopted as the machine learning algorithm for channel estimation shown in Figure 2 to adaptively improve the BER response relative to increasing SNR and the channel condition considering a typical white LED driving voltage of 3.5V [22][23].…”

A Novel Adaptive OFO-OFDM Modulation for Visible Light Communication

“…As the signal amplitude voltage increases, the scheme is seen to be more power efficient since there is higher percentage of the probability that the scheme will utilize less power. To justify the performance superiority of the proposed OFO scheme, the BER performance is validated by the four modulation constellations supported by wideband standard (4QAM, 16QAM, 64QAM and 256QAM) respectively [42]. The modulation constellations are required for bit mapping regardless of the nature of the signal (complex or real) being processed.…”

“…Although OFO and FLIP shows similarity in power handling, the adaptive capability of OFO guarantees enormous improvement over the conventional techniques in achieving a much higher average throughput. The proposed OFO algorithm is further validated by comparing the average throughput performance relative to the average throughput of its adaptive radio frequency counterparts in [35,42,44] under comparable operating conditions. To model similar operating condition, the transmit power used in [35,42,44] was estimated by equitable distribution of the allocated average transmit power in the proposed OFO algorithm to the total number of subcarriers.…”

“…The proposed OFO algorithm is further validated by comparing the average throughput performance relative to the average throughput of its adaptive radio frequency counterparts in [35,42,44] under comparable operating conditions. To model similar operating condition, the transmit power used in [35,42,44] was estimated by equitable distribution of the allocated average transmit power in the proposed OFO algorithm to the total number of subcarriers. Result in Figure 14 and Table 2 showed that the proposed algorithm outperformed the existing algorithms with an appreciable improvement in the average throughput.…”

“…The transmit signal is modelled as a Gaussian distribution with zero mean based on the central limit theorem as stipulated by [25], given that the transmitted time-domain samples will be approximately equivalent to a Gaussian distribution when the total number of subcarriers is sufficiently large, for N≥64, and variance 2 with electrical and optical powers of ( 2 ) and ( ) respectively. The channel impulse response and the power delay profile are derived from [35,41] and the modulations (4QAM, 16QAM, 64QAM and 256QAM) supported by wideband standard [42] are adapted for the purpose of validation of the BER performance. The conventional multicarrier schemes as well as the proposed algorithm's simulation parameters are derived directly from the model's formulations.…”