A wide range of wireless sensor network applications are characterized by local processing of the sensed data and only meager data communication requirements. Indeed, because sensor nodes are battery powered and wirel...
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The digital compensation of RF imperfections is promising, but requires accurate models for the influence of the impairments on the baseband signals. To this end, this paper proposes a model for imperfections occurrin...
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The digital compensation of RF imperfections is promising, but requires accurate models for the influence of the impairments on the baseband signals. To this end, this paper proposes a model for imperfections occurring in the popular direct conversion receiver architecture. It extends the previously applied IQ imbalance models by also taking DC offsets and nonlinearities from the output stage of the mixer up to the input stage of the ADC into account. Moreover, the impact of this more extended impairment model on the received baseband signals is derived. Finally, an estimation algorithm is presented to estimate the parameters of this model for digital compensation of the influence of these imperfections. Numerical results show that this estimation approach can achieve accurate estimates of the impairment parameters.
A wide range of wireless sensor network applications are characterized by local processing of the sensed data and only meager data communication requirements. Indeed, because sensor nodes are battery powered and wirel...
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A wide range of wireless sensor network applications are characterized by local processing of the sensed data and only meager data communication requirements. Indeed, because sensor nodes are battery powered and wireless communication bears a high energy cost, data transmission can be traded for on-the-node computation to extend node and network lifetime. Furthermore, the energy consumption can be reduced significantly by selecting and realizing the application on an appropriate processing element. In this article, we propose a new statistical technique for energy consumption estimation for a specific application on various platforms. We have empirically verified the methodology on various classes of embedded processors commonly used in sensor nodes. The methodology can also be applied to multiprocessor platforms. Our solution is not only capable to achieve high accuracy but also facilitates the application developer to evaluate different platforms without actually implementing the application on each of these platforms. Our experimental evaluation results for various platforms will help to understand the implications of using different processing elements and their effects on the lifetime of the network.
This work investigates the joint impact of quantization and clipping, caused by analog-to-digital converters (ADCs) with low bit resolutions, on single- and multi-carrier block transmission systems in wireless multipa...
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This work investigates the joint impact of quantization and clipping, caused by analog-to-digital converters (ADCs) with low bit resolutions, on single- and multi-carrier block transmission systems in wireless multipath environments. We consider single carrier block transmission with frequency domain equalization (SC-FDE) and the multi-carrier techniques OFDM and MC-CDMA. By approximating the ADC input as Gaussian distributed, the effective signal-to-noise ratio in the received signal and decision variables are derived and analyzed. The bit-error rate (BER) performance is simulated and compared for various constellations under different multipath conditions. The results reveal that frequency diversity is an effective measure to combat the joint impact of quantization and clipping. For the ADCs with moderate resolution bits, i.e., R = 5 and 4 bits, SC-FDE is shown to achieve the same performance as MC-CDMA. It is noted that due to the applied Gaussian approximation for the received signals, the derived SC-FDE results provide a lower bound on the performance of the systems under the influence of the ADC nonlinearity. This bound is tight, however, in case of rich multipath environments.
Dealing with radio frequency (RF) front-end impairments will be one of the major design challenges for next-generation wireless communication systems due to conflicting requirements, such as high data rate, low cost a...
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Dealing with radio frequency (RF) front-end impairments will be one of the major design challenges for next-generation wireless communication systems due to conflicting requirements, such as high data rate, low cost and low power consumption. The use of digital compensation of the imperfections appears a very promising method to meet specifications. Pursuing that path, however, requires thorough understanding of the influence of the RF front-end non-idealities on the received signal and the resulting system performance. To this end, this paper reviews the impact of three important impairments, namely, phase noise, IQ imbalance and nonlinearities, on the performance of next-generation high-rate wireless systems. A specific focus is on the difference between transmitter (TX) and receiver (RX) incurred imperfections. Moreover, a generalized error model to capture to aggregate influence of different impairments is presented.
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