Low complexity spectrum sensing for cognitive radio enabled aeronautical communication systems

Air traffic has seen tremendous growth over the last decade and is expected to grow continuously. The state of the art of current aeronautical communication system is not capable of handling future developments due to the scarcity of the spectrum resources and demands enhanced air traffic management schemes. The L-band Digital Aeronautical Communication System (LDACS) is gaining traction as a scheme of choice and aims to exploit the capabilities of modern digital communication techniques and computing architectures. To improve the quality of air traffic management, the spectrum required to be used efficiently. Cognitive Radio (CR) based approaches have also been proposed for LDACS to improve spectrum efficiency and communication capacity. The CR-based system enables opportunistic and on-demand access to L-band channel(s) while meeting the reliability and safety requirements. This allows an aircraft to identify vacant spectral bands in the air-to-ground spectrum using spectrum sensing techniques and choose the proper channel to initiate an LDACS air-to-ground transmission, similar to the case with ground-based CRs. However, spectrum sensing for LDACS presents unique challenges compared to terrestrial systems; aircraft in the range of the system is always in motion resulting in a continually varying network structure, while the channel conditions between the communicating entities can change very rapidly, requiring much more complex processing compared to terrestrial CR systems. At the same time, the limited energy budget of the aircraft demands low complexity techniques to improve energy efficiency. Computationally efficient, fast, and reliable detection techniques that perform well in low signal-to-noise ratio and noise uncertainty scenarios are required in LDACS. New spectrum sensing algorithms and their low complexity implementations are proposed in this thesis to address the aforementioned challenges. The first work presents an energy-difference detection-based spectrum sensing scheme for CR-enabled LDACS system. The detection method utilizes the unique shape of the spectrum after removing the legacy system signals from the known spectral gaps. Irregularities of the power spectrum density across continuous narrow bands are detected by comparing the absolute energy difference of the neighbouring LDACS and legacy channels with a predefined decision threshold. Simulation studies show that the proposed energy-difference detection based sensing scheme offers improved detection performance than the conventional Energy Detection (ED) scheme at the low SNR scenarios and identical performance at relatively high SNRs. Though the technique improves the detection accuracy, it suffers from higher computational complexity, also the scheme is applicable only for the sensing of the LDACS spectrum. An adaptive energy detection scheme is proposed as the second work to reduce the computational complexity further, and to provide a generic sensing scheme. In this technique, the historical energy observations from previous sensing epochs are adaptively used to improve the detection accuracy. An enhanced real-time noise variance estimation technique is developed with the aid of cyclic prefix in the LDACS signals. The noise variance can be estimated effectively in real-time irrespective of the primary signal being on or off. The proposed technique does not incur dedicated hardware blocks for noise variance estimation, leading to an efficient hardware implementation of the scheme without significant resource overheads. The proposed technique is integrated into a cognitive radio platform on a field-programmable gate array (FPGA) device to quantify resource overheads. Results of simulation studies show that the scheme provides better detection accuracy compared to the existing ED techniques. To reduce the SNR wall to a lower value compared to the first and second works using the prior knowledge of the preamble signals, a multiplier-less correlator based sensing scheme is proposed. The proposed correlator can also serve as the receiver synchronizer for the LDACS air-to-ground links. The architecture is designed in such a way that it can cater to the preamble structure of LDACS air-to-ground transmissions. The computational precision of the system is enhanced to improve the performance in very low SNR conditions. The proposed architecture offers improved detection performance over traditional energy detection even at low SNR with lower energy consumption than a multiplier-based correlator, while also assisting in receiver synchronization. A simplified cyclostationary detection (CD) scheme is proposed as the fourth work to get the best trade-off between accuracy, complexity, and sensing duration. In this scheme, a sliding correlation-based CD is proposed. The test statistic is a likelihood ratio test (LRT) in which the cyclostationary feature is normalized with the real-time noise variance. The proposed scheme is implemented in Verilog and mapped on a Xilinx FPGA device to quantify the overall resource consumption. Results show that the scheme offers comparable detection performance with the multiplier-less correlator with only one-third of resource overheads and power consumption and better performance than the conventional CD schemes. Wideband spectrum sensing is essential to find the different possible spectral holes in the frequency spectrum of interest. Conventional Nyquist wideband sensing is not a power-efficient solution as it requires massive computing capability due to the higher sampling and quantization and for subsequent processing. In this context, a power-efficient wideband spectrum sensing is proposed to alleviate this issue by providing the best accuracy-complexity trade-off. The current research proposes and implements a wideband sensing architecture based on a one-bit quantization at the CR receiver. A Finite Impulse Response (FIR) filter bank is used to split the wideband to several narrow bands; then, the detection algorithm is applied to each narrow-bands individually. In the proposed scheme, the sampling and quantization unit is reduced to a high-speed comparator, and the multiplication in each filter tap is replaced by a sign changer, which is implemented using a 2’s complement circuit and a 2:1 multiplexer. The scheme considerably reduces the computational complexity of the conventional filter bank based sensing by using a sign changer instead of a multiplier.Doctor of Philosoph

Efficient spectrum sensing for aeronautical LDACS using low-power correlators

Air traffic has seen tremendous growth over the last decade pushing the need for enhanced air traffic management schemes. L-band Digital Aeronautical Communication System (LDACS) is gaining traction as a scheme of choice, and aims to exploit the capabilities of modern digital communication techniques and computing architectures. Cognitive radio based approaches have also been proposed for LDACS to improve spectrum efficiency and communication capacity; however, these require intelligent compute capability in aircrafts that enforce limited space and power budgets. This paper proposes the use of multiplierless correlation to enable spectrum sensing in LDACS air-to-ground links, and its integration into the on-board LDACS system. The proposed architecture offers improved performance over traditional energy detection even at low signal to noise ratio (SNR) with lower energy consumption than a multiplier-based correlator, while also assisting in receiver synchronisation. We evaluate the proposed architecture on a Xilinx Zynq FPGA and show that our approach results in 28.3% reduction in energy consumption over the multiplier-based approach. Our results also show that the proposed architecture offers 100% accuracy in detection even at -12dB SNR without requiring additional circuitry for noise estimation, which are an integral part of energy detection based approaches

An energy-difference detection based spectrum sensing technique for improving the spectral efficiency of LDACS1 in aeronautical communications

European Organization for the Safety of Air Navigation (EUROCONTROL) has proposed to use the part of L-band for future Air-to-Ground (A/G) communications. Two technology options are available for the proposed L-band digital aeronautical communication system (LDACS); LDACS1 and LDACS2. LDACS1 is considered as the most promising and matured candidate for future A/G communications. There is an agreement on European level to only consider LDACS1 further and LADCS1 is also referred to as LDACS. The efficiency of LDACS1 can be increased by the dynamic allocation of spectrum in an opportunistic fashion, which would require spectrum sensing to detect available frequency bands. In this paper, we propose an energy-difference detection based spectrum sensing scheme for cognitive radio enabled LDACS1 system. A mathematical formulation for the probability of detection, the probability of false alarm and the decision threshold in Additive White Gaussian Noise (AWGN) channel are derived for the proposed scheme. Simulation study shows that the proposed energy-difference detection based sensing scheme offers an improved detection performance than the conventional energy detection method at the low Signal-to-Noise Ratio (SNR) scenarios and identical performance at relatively high SNRs.Accepted versio

A cyclic prefix assisted spectrum sensing method for aeronautical communication systems

Continuous growth of air-traffic demands new technologies for future aeronautical communication systems. L-band Digital Aeronautical Communications System (LDACS) is considered as a potential candidate for the future air-to-ground links. Spectrum utilization efficiency of LDACS can be improved by enabling dynamic spectrum access (DSA) in the system. In this context, the present paper proposes a novel cyclostationary feature detection scheme based on the periodicity of the autocorrelation of LDACS signals for spectrum sensing, which is key requirement in DSA. A wideband spectrum sensing simulation model is developed to evaluate the detection performance of the proposed scheme. To improve the adaptability of the spectrum sensing unit to variable wide bandwidth, the proposed system uses interpolation and masking based filters that can extract individual LDACS channels from the wide-band signals. Results of simulation studies show that the proposed scheme provides better detection accuracy against the conventional cyclostationary feature detection scheme and energy detection scheme, while maintaining the false alarm rates to an acceptable level which balances the overall throughput of the system.Accepted versio

GAE and OBE Enhanced Interference Mitigation Techniques in LDACS

Interference mitigation in L-band digital aeronautic communication systems from legacy users is vital due to stringent safety requirements and steady-state increase in air traffic. This paper proposes an L-band digital aeronautic communication systems receiver prototype that employs nonlinear operations to reduce the interference from the prime interference contributor distance measuring equipment. The knowledge of genie-aided estimator and optimum Bayesian estimator is utilized to propose improved and low complexity nonlinear devices, such as a genie-aided estimator enhanced pulse peak attenuator, genie-aided estimator enhanced pulse peak limiter, joint genie-aided estimator enhanced pulse peak attenuator, joint genie-aided estimator enhanced pulse peak limiter, optimum Bayesian estimator enhanced pulse peak attenuator, optimum Bayesian estimator enhanced pulse peak limiter, joint optimum Bayesian estimator enhanced pulse peak attenuator and joint optimum Bayesian estimator enhanced pulse peak limiter. The performance of the proposed methods is compared with the classical pulse blanking in terms of the received bit error rate for different signal-to-noise ratios. The proposed genie-aided estimator enhanced methods exhibited SNR saving in the range of 2 to 2.5 dB at a bit error rate of 10−1. At the same BER, the proposed optimum Bayesian estimator enhanced methods achieved SNR saving in the range of 2.5 to 3 dB

Efficient spectrum sensing for aeronautical LDACS using low-power correlators

Air traffic has seen tremendous growth over the past decade pushing the need for enhanced air traffic management schemes. The $L$ -band digital aeronautical communication system (LDACS) is gaining traction as a scheme of choice, and aims to exploit the capabilities of modern digital communication techniques and computing architectures. Cognitive radio-based approaches have also been proposed for LDACS to improve spectrum efficiency and communication capacity; however, these require intelligent compute capability in aircrafts that enforce limited space and power budgets. This paper proposes the use of multiplierless correlation to enable spectrum sensing in LDACS air-to-ground links, and its integration into the on-board LDACS system. The proposed architecture offers improved performance over traditional energy detection (ED) even at low signal-to-noise ratio (SNR) with lower energy consumption than a multiplier-based correlator, while also assisting in receiver synchronization. We evaluate the proposed architecture on a Xilinx Zynq field-programmable gate array and show that our approach results in 28.3% reduction in energy consumption over the multiplier-based approach. Our results also show that the proposed architecture offers 100% accuracy in detection even at -12-dB SNR without requiring additional circuitry for noise estimation, which are an integral part of ED-based approaches.Accepted versio

A power-efficient spectrum-sensing scheme using 1-bit quantizer and modified filter banks

Spectrum sensing is an efficient way to determine the spectrum availabilities over the frequency range of interest, aiding in improving the spectrum utilization in the cognitive radio (CR) systems. Conventional Nyquist multiband sensing entails higher computational capability for sampling, quantization, and subsequent processing, lending the approach infeasible for applications with limited power budgets. In this brief, a power-efficient spectrum-sensing technique is proposed, which explores an accuracy-complexity tradeoff. The presented spectrum-sensing architecture is based on 1-bit quantization at the CR receiver and implements it in hardware by a resource- and power-efficient approach, using a finite-impulse-response (FIR) filter-bank channelizer. The proposed scheme allows the complex operators like multipliers and quantizers to be replaced by the inverter logic and high-speed comparators, reducing the hardware complexity and power consumption. We validate the proposed scheme on a field-programmable gate-array (FPGA) emulator for an aeronautical L-band digital aeronautical communication system (LDACS) application, and our results show that the proposed scheme achieves substantial resource reduction with at most 5% degradation in the detection accuracy in this case.Accepted versio

An adaptive energy detection scheme with real-time noise variance estimation

Energy detection-based spectrum sensing techniques are ideally suited for power-constrained cognitive radio applications because of their lower computational complexity compared to feature detection techniques. However, their detection performance is dependent on multiple factors like accuracy of noise variance estimation and signal-to-noise ratio (SNR). Many variations of energy detection techniques have been proposed to address these challenges; however, they achieve the desired detection accuracy at the cost of increased computational complexity. This restricts the use of enhanced energy detection schemes in power-constrained applications such as aeronautical communication. In this paper, an adaptive low-complexity energy detection scheme is proposed for spectrum sensing in an L-band Digital Aeronautical Communication System (LDACS) at lower SNR levels. Our scheme uses a real-time noise variance estimation technique using autocorrelation which is induced by the cyclic prefix property in LDACS signals. The proposed technique does not incur dedicated hardware blocks for noise variance estimation, leading to an efficient hardware implementation of the scheme without significant resource overheads. The simulation studies of the proposed scheme show that the desired accuracy (90% detection accuracy with only 10% of false alarms) can be achieved even at −16.5 dB SNR, significantly lowering the SNR wall over existing energy detection schemes.Accepted versio