Channel Magnitude Based Energy Detection With Receive Diversity for Multi-Level Amplitude-Shift Keying in Rayleigh Fading

A novel low complexity energy detection receiver, which utilizes knowledge of the magnitudes of the fading gains of the receive diversity branches, is presented. Its error performance in flat Rayleigh fading with multi-level amplitude-shift keying is analyzed, resulting in a closed form expression for the symbol error probability (SEP) as well as analytical results for high signal-to-noise ratios. These show that the receiver has the same diversity order as that of coherent receivers but maintains the low complexity structure of energy detectors. Numerical results show that the SEP performance of the energy detection receiver is much closer to that of a coherent receiver than to that of a noncoherent one. Furthermore, we also consider transmit constellation optimization and conclude that an equally spaced amplitude level constellation performs close to the optimal solution in Rayleigh fading. A significant advantage of this receiver is that it performs much better than noncoherent detection but maintains the low complexity structure of noncoherent detectors. Training to obtain the channel magnitudes is, however, required but the low complexity receiver can be used to perform that with the only additional overhead being the training time.

[1]  Vladan Velisavljevic,et al.  Threshold Optimization for Energy Detection-Based Spectrum Sensing Over Hyper-Rayleigh Fading Channels , 2015, IEEE Communications Letters.

[2]  H. Urkowitz Energy detection of unknown deterministic signals , 1967 .

[3]  Armin Wittneben,et al.  Nonlinear MIMO: affordable MIMO technology for wireless sensor networks , 2010, IEEE Transactions on Wireless Communications.

[4]  Geoffrey Ye Li,et al.  A survey of energy-efficient wireless communications , 2013, IEEE Communications Surveys & Tutorials.

[5]  Armin Wittneben,et al.  sMILE: The First MIMO Envelope Detection Testbed , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).

[6]  Ranjan K. Mallik,et al.  Optimal Multilevel ASK With Noncoherent Diversity Reception in Uncorrelated Nonidentical and Correlated Rayleigh Fading , 2016, IEEE Transactions on Communications.

[7]  Ranjan K. Mallik,et al.  Noncoherent Reception of Multi-Level ASK in Rayleigh Fading with Receive Diversity , 2014, IEEE Transactions on Communications.

[8]  Emil Björnson,et al.  Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits , 2013, IEEE Transactions on Information Theory.

[9]  J. Gil-Pelaez Note on the inversion theorem , 1951 .

[10]  Aarne Mämmelä,et al.  Error performance of PAM systems using energy detection with optimal and suboptimal decision thresholds , 2011, Phys. Commun..

[11]  Ranjan K. Mallik,et al.  Signal Design for Multiple Antenna Systems With Spatial Multiplexing and Noncoherent Reception , 2015, IEEE Transactions on Communications.

[12]  Armin Wittneben,et al.  Channel Estimation for Very Low Power MIMO Envelope Detectors , 2010, 2010 IEEE International Conference on Communications.

[13]  Xiaofan Li,et al.  Energy Detection Based Spectrum Sensing for Cognitive Radios Over Time-Frequency Doubly Selective Fading Channels , 2015, IEEE Transactions on Signal Processing.

[14]  Lie-Liang Yang,et al.  Low-complexity noncoherent fusion rules for wireless sensor networks monitoring multiple events , 2014, IEEE Transactions on Aerospace and Electronic Systems.

[15]  Roberto Garrappa,et al.  Some Formulas for Sums of Binomial Coefficients and Gamma Functions , 2007 .

[16]  Jason Cong,et al.  Analysis of Noncoherent ASK Modulation-Based RF-Interconnect for Memory Interface , 2012, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[17]  Il-Min Kim,et al.  Noncoherent Amplify-and-Forward Cooperative Networks: Robust Detection and Performance Analysis , 2013, IEEE Transactions on Communications.

[18]  Armin Wittneben,et al.  Diversity and spatial multiplexing of MIMO amplitude detection receivers , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

[19]  Alex B. Gershman,et al.  Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals , 2006, IEEE Transactions on Signal Processing.

[20]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[21]  Sumei Sun,et al.  Energy-Efficient, Large-Scale Distributed-Antenna System (L-DAS) for Multiple Users , 2013, IEEE Journal of Selected Topics in Signal Processing.

[22]  W. Osborne,et al.  Coherent and Noncoherent Detection of CPFSK , 1974, IEEE Trans. Commun..

[23]  Yonghong Zeng,et al.  Blindly Combined Energy Detection for Spectrum Sensing in Cognitive Radio , 2008, IEEE Signal Processing Letters.

[24]  Sithamparanathan Sabesan,et al.  Wide Area Passive UHF RFID System Using Antenna Diversity Combined With Phase and Frequency Hopping , 2014, IEEE Transactions on Antennas and Propagation.

[25]  Ming Li,et al.  Blind Energy-based Detection for Spatial Spectrum Sensing , 2015, IEEE Wireless Communications Letters.

[26]  Qian He,et al.  Energy-efficient noncoherent signal detection for networked sensors using ordered transmissions , 2011, 2011 45th Annual Conference on Information Sciences and Systems.

[27]  Aarne Mämmelä,et al.  Energy Detection of Multilevel PAM Signals with Systematic Threshold Mismatch , 2009, J. Electr. Comput. Eng..

[28]  Rui Zhang,et al.  Wireless powered communication: opportunities and challenges , 2014, IEEE Communications Magazine.