Achievable Rate and Capacity Analysis for Ambient Backscatter Communications

In this paper, we analyze the achievable rate for ambient backscatter communications under three different channels: the binary input and binary output (BIBO) channel, the binary input and signal output (BISO) channel, and the binary input and energy output (BIEO) channel. Instead of assuming Gaussian input distribution, the proposed study matches the practical ambient backscatter scenarios, where the input of the tag can only be binary. We derive the closed-form capacity expression as well as the capacity-achieving input distribution for the BIBO channel. To show the influence of the signal-to-noise ratio (SNR) on the capacity, a closed-form tight ceiling is also derived when SNR turns relatively large. For BISO and BIEO channel, we obtain the closed-form mutual information, while the semi-closed-form capacity value can be obtained via one dimensional searching. Simulations are provided to corroborate the theoretical studies. Interestingly, the simulations show that: (i) the detection threshold maximizing the capacity of BIBO channel is the same as the one from the maximum likelihood signal detection; (ii) the maximal of the mutual information of all channels is achieved almost by a uniform input distribution; and (iii) the mutual information of the BIEO channel is larger than that of the BIBO channel, but is smaller than that of the BISO channel.

[1]  Shi Jin,et al.  Symbol detection and performance analysis of the ambient backscatter system , 2016, 2016 IEEE/CIC International Conference on Communications in China (ICCC).

[2]  Donatella Darsena,et al.  Modeling and Performance Analysis of Wireless Networks With Ambient Backscatter Devices , 2017, IEEE Transactions on Communications.

[3]  Yiyang Pei,et al.  Modulation in the Air: Backscatter Communication Over Ambient OFDM Carrier , 2017, IEEE Transactions on Communications.

[4]  Upamanyu Madhow,et al.  On the limits of communication with low-precision analog-to-digital conversion at the receiver , 2009, IEEE Transactions on Communications.

[5]  Jing Qian,et al.  Signal detection of ambient backscatter system with differential modulation , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[6]  Caijun Zhong,et al.  Symbol Detection of Ambient Backscatter Systems With Manchester Coding , 2018, IEEE Transactions on Wireless Communications.

[7]  Hongbo Zhu,et al.  Semi-Coherent Detection and Performance Analysis for Ambient Backscatter System , 2016, IEEE Transactions on Communications.

[8]  Shi Jin,et al.  Capacity of Ambient Backscatter Communications with Binary Input and Binary Output Channel , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[9]  Milton Abramowitz,et al.  Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .

[10]  Chintha Tellambura,et al.  Ambient Backscatter Communication Systems: Detection and Performance Analysis , 2016, IEEE Transactions on Communications.

[11]  Ying-Chang Liang,et al.  Cooperative Ambient Backscatter Communications for Green Internet-of-Things , 2018, IEEE Internet of Things Journal.

[12]  Laurence T. Yang,et al.  The Internet of Things: From RFID to the Next-Generation Pervasive Networked Systems , 2008 .

[13]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[14]  Angli Liu,et al.  Turbocharging ambient backscatter communication , 2014, SIGCOMM.

[15]  R. Gallager Information Theory and Reliable Communication , 1968 .

[16]  Hongbo Zhu,et al.  Noncoherent Detections for Ambient Backscatter System , 2017, IEEE Transactions on Wireless Communications.

[17]  Zhu Han,et al.  Ambient Backscatter: A New Approach to Improve Network Performance for RF-Powered Cognitive Radio Networks , 2017, IEEE Transactions on Communications.

[18]  David Wetherall,et al.  Ambient backscatter: wireless communication out of thin air , 2013, SIGCOMM.

[19]  Hongbo Zhu,et al.  Semi-coherent detector of ambient backscatter communication for the Internet of Things , 2017, 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[20]  Arnab Raha,et al.  Powering the Internet of Things , 2014, 2014 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

[21]  Saman Atapattu,et al.  Channel capacity and lower bound for ambient backscatter communication systems , 2017, 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP).

[22]  Ira S. Moskowitz Approximations for the capacity of binary input discrete memoryless channels , 2010, 2010 44th Annual Conference on Information Sciences and Systems (CISS).