SATCOM link adaptive configuration design in radio frequency interference environment

Radio frequency interference (RFI) is ubiquitous in wireless communications which could greatly degrade communication system performances in an open environment. For satellite communications (SATCOM), the system performances degradation could be even worse considering the large round trip time (RTT) delay. To mitigate RFI effects, cognitive radio with adaptive waveform configurations could be effective. To quantify the cognitive radio system performance, spectral efficiency and energy efficiency are two metrics. Spectral efficiency (SE), defined as the average data rate per unit bandwidth, quantifies how efficiently the available spectrum is utilized. Energy efficiency (EE), defined as the successful transmitted information bits per unit energy from transmitter to receiver, quantifies how efficiently the energy is utilized. However, the two metrics construct a fundamental trade-off in communication system design. Basically, with higher average energy per bit to noise power spectral density ratio at the receiver, the packet can be more successfully detected, thus utilizing the spectrum more efficiently, giving higher SE; which however requires more energy, lowering EE, and vice versa. In this paper, we design adaptive configuration of SATCOM link operating in the RFI environment, and study the system trade-off between SE and EE, by greatly exploiting cognitive radio configurability for SATCOM interference mitigation capability. A general metric SEE (Spectral/Energy Efficiency), which quantifies the preference of SE or EE, has been formulated with practical system parameters, including information bit length, overhead bits, modulation and channel coding schemes, frequency hopping, wireless channel conditions, frame retransmissions, etc, to facilitate the system analysis. A closed-form solution for information bits rate control is obtained in various RFI environments. An iteration algorithm is presented for cognitive radio joint transmission power control, information bits rate control, and modulation and channel coding adaptation, to optimize the system performances in the RFI environment.

[1]  Gang Wang,et al.  Hybrid onboard and ground based digital channelizer beam-forming for SATCOM interference mitigation and protection , 2016, SPIE Defense + Security.

[2]  Hyuck M. Kwon,et al.  MIMO Cognitive Radio User Selection With and Without Primary Channel State Information , 2016, IEEE Transactions on Vehicular Technology.

[3]  Xiang-Gen Xia,et al.  Iterative Eigenvalue Decomposition and Multipath-Grouping Tx/Rx Joint Beamformings for Millimeter-Wave Communications , 2015, IEEE Transactions on Wireless Communications.

[4]  Gang Wang,et al.  Energy Efficiency and Spectral Efficiency Tradeoff in Type-I ARQ Systems , 2014, IEEE Journal on Selected Areas in Communications.

[5]  Gang Wang,et al.  Robust airborne image transmission using joint source-channel coding with UEP , 2016, 2016 IEEE Aerospace Conference.

[6]  Frank G. Shi,et al.  2.4 GHZ HETERODYNE RECEIVER FOR HEALTHCARE APPLICATION , 2016 .

[7]  Wei Cai,et al.  2.4GHZ Class AB power Amplifier For Healthcare Application , 2016, ArXiv.

[8]  H. Nikookar,et al.  Cognitive radio modulation techniques , 2008, IEEE Signal Processing Magazine.

[9]  Lun Li,et al.  Blind Detection with Unique Identification in Two-Way Relay Channel , 2012, IEEE Transactions on Wireless Communications.

[10]  Sergio Verdú,et al.  Spectral efficiency in the wideband regime , 2002, IEEE Trans. Inf. Theory.

[11]  Gang Wang,et al.  An accurate frame error rate approximation of coded diversity systems with non-identical diversity branches , 2014, 2014 IEEE International Conference on Communications (ICC).

[12]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization , 2005, IEEE Transactions on Wireless Communications.

[13]  Gang Wang,et al.  Cognitive radio unified Spectral efficiency and Energy Efficiency trade-off analysis , 2015, MILCOM 2015 - 2015 IEEE Military Communications Conference.

[14]  Anant Sahai,et al.  Towards a Communication-Theoretic Understanding of System-Level Power Consumption , 2011, IEEE Journal on Selected Areas in Communications.

[15]  大島 利雄 An elementary approach to the Gauss hypergeometric function , 2013 .

[16]  Erik Blasch,et al.  SINR estimation for SATCOM in the environment with jamming signals , 2016, SPIE Defense + Security.

[17]  Gang Wang,et al.  Optimum Design for Robustness of Frequency Hopping System , 2014, 2014 IEEE Military Communications Conference.

[18]  Norman C. Beaulieu,et al.  NDA estimation of SINR for QAM signals , 2005, IEEE Communications Letters.

[19]  Ivan Howitt,et al.  Realistic energy model based energy balanced optimization for Low Rate WPAN network , 2009, IEEE Southeastcon 2009.

[20]  Eitan Altman,et al.  A jammer's dilemma: Where and how to jam , 2012, 2012 6th International Conference on Network Games, Control and Optimization (NetGCooP).

[21]  Gang Wang,et al.  Optimum Energy- and Spectral-Efficient Transmissions for Delay-Constrained Hybrid ARQ Systems , 2016, IEEE Transactions on Vehicular Technology.

[22]  Gang Wang,et al.  Spread spectrum design for aeronautical communication system with radio frequency interference , 2015, 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC).

[23]  Jingxian Wu,et al.  Cross-layer design of energy efficient coded ARQ systems , 2012, GLOBECOM.

[24]  Gang Wang,et al.  Energy and spectral efficient transmissions of coded ARQ systems , 2013, 2013 IEEE International Conference on Communications (ICC).

[25]  Wei Cai,et al.  Optimization of a GPU Implementation of Multi-Dimensional RF Pulse Design Algorithm , 2011, 2011 5th International Conference on Bioinformatics and Biomedical Engineering.