EFFECTIVE CROSS-LAYER SATELLITE COMMUNICATIONS LINK INTERFERENCES MITIGATION IN THE PRESENCE OF VARIOUS RFI TYPES

Abstract

A systematic interferences mitigation design for protected satellite communications (SATCOM) is provided. An advanced channel coding is designed to provide coding gain for SATCOM even in the presence of synchronization errors due to the effect of radio frequency interferences (RFIs). A unified SATCOM system spectrum efficiency and energy efficiency method is developed with a unified interference model for SATCOM dynamic resource allocation (DRA). The SATCOM system DRA is designed with a game theoretic engine and optimizations providing traffic control, power control, and modulation and coding agile waveform adaptations. The interferences mitigation design is implemented with software defined radio USRP and GNU-radio to maintain communication link quality of services (QoS).

Description

FIELD OF THE DISCLOSURE

The present disclosure generally relates to the field of cognitive radio transmission, reception, and dynamic control, for satellite communications (SATCOM) in a Radio Frequency Interference (RFI) environment. More particularly, the disclosure relates to anti-jamming methods and a cognitive radio testbed apparatus in SATCOM.

BACKGROUND

In the satellite communications (SATCOM) infrastructure, both space-borne and hybrid space-terrestrial systems will require assured connection capabilities, enhanced defensive control, and robust performance to support complex collaborative missions.

Wideband geosynchronous orbit (GEO) SATCOM can provide high-capacity and long haul communications for various terrestrial applications, industry operations, and interested users. GEO SATCOM continuous operation is critical to individual, cooperation, and government operations.

Each GEO satellite provides services in both the X and Ka frequency bands, with the capability to cross-band between the two frequencies onboard the satellite. It features an electrically steerable and phased array X-band, a mechanically steered Ka-band, and a fixed earth-coverage X-band. These wideband SATCOM networks entail extreme complexity, operating environment unpredictability, and interference susceptibility.

Therefore, it is essential to develop cognitive spectrum management solutions that are not only context-aware and capable of learning and probing for subscriber distributions, quality of services, mission priorities and traffic patterns, but also agile in waveform adaptation to provide active countermeasures for persistent and adaptive RF interferences (RFI).

In addition, to provide accurate and reliable performance evaluation results to guide cognitive spectrum SATCOM development, abstracted system models must be built practically to evaluate various important techniques, including frequency-hopping spread spectrum (FHSS), channel coding, and anti-jamming capability. The practical models include FHSS and unified interferences model. The performance evaluation metric is unified system spectrum efficiency and system energy efficiency.

BRIEF SUMMARY OF THE DISCLOSURE

One aspect or embodiment of the present disclosure includes cross-layer design for anti-jamming methods in a satellite communication (SATCOM) system. Various network traffic packets are firstly partitioned as frames, which are processed with baseband signaling system parameters. With the signaling configuration, information bits are encoded with forward error correction (FEC) scheme. The bits are then formed into symbols based on the bit-to-symbol mapping scheme. To avoid severe interferences, frequency hopping (FH) is applied. For further interferences mitigation, beamforming is applied to transmit the signal in a desired direction. At the receiver, interference nulling or an equivalent scheme is applied to reduce the intentional interferences power. Afterwards, the frequency de-hopping and synchronizations are performed to transform the radio frequency signal to baseband signal. Symbol de-mapping and FEC decoding is then performed for the link performance measurement.

In response to interferences, a game reasoning process is performed to configure system parameters including transmission power, traffic data rate, modulation and coding (MODCOD), and the beamforming precoding matrix, to provide a cross-layer anti-jamming adaptive waveform.

Optionally, different FEC schemes are applied in light or heavy interferences environments for quality of services (QoS) improvement while maintaining low recovering complexity.

Optionally, the waveform modulation is performed to transmit the signal in one of a number of frequency bands.

Optionally, beamforming is applied for multiple antennas transmitter to enhance directional performance.

Optionally, the interferences of narrowband interference, wideband interference, radar sources, and intelligence jammers states can be estimated via space object automatic target detection, recognition, and classification methods.

Optionally, the interferences are classified as both intentional and unintentional interferences.

Optionally, interference nulling at a receiver is performed for multiple antennas receiver configurations or omitted for single antenna system.

Optionally, a game reasoning process obtains the following information: a space object propagator provides the location and a speed of a current satellite in the SATCOM system; a SATCOM performance evaluation toolkit determines the link budget information, and the spectrum sensing determines the situational awareness of the current SATCOM link.

Optionally, in the game reasoning process, a transmission pair and adversaries are included.

Optionally, the game reasoning process is implemented by, the transmitter, the receiver, and the jammers, each including a Universal Software Radio Peripheral (USRP) configured with Gnu's not Unix (GNU) Radio.

Optionally, each player obtains the information of the opponent by spectrum sensing and signal detection.

Optionally, the traffic includes voice traffic, video traffic, image traffic, and text.

Optionally, the waveform of the source data includes a wideband GEO SATCOM waveform transmitted in the SATCOM system via GEO satellites.

Optionally, after the anti-jamming adaptive waveform is selected by the game engine, the anti-jamming waveform is then transmitted with the signaling by the transmitter to the receiver, which is then demodulated and decoded for information recovery.

Optionally, performance measurements include the frame error rate, system outage, spectrum efficiency, and energy efficiency.

Other aspects or embodiments of the present disclosure can be understood by those skilled in the art in light of the description, the claims, and the drawings of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings are merely examples for illustrative purposes according to various disclosed embodiments and are not intended to limit the scope of the present disclosure.

FIG. 1 depicts a system block diagram illustrating exemplary cross-layer design anti-jamming scheme in satellite communication (SATCOM) system according to various disclosed embodiments;

FIG. 2 depicts a block diagram illustrating an exemplary enhanced SATCOM channel coding scheme according to various disclosed embodiments;

FIG. 3 depicts a Bose-Chaudhuri (BCH) coding scheme according to various disclosed embodiments;

FIG. 4 depicts cognitive radio adaptive configurations according to various disclosed embodiments; and

FIG. 5 depicts an exemplary cognitive radio testbed apparatus for implementing exemplary anti-jamming methods in a SATCOM system according to various disclosed embodiments.

DETAILED DESCRIPTION

Reference will now be made in detail to exemplary embodiments of the disclosure, which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. In the following description, reference is made to the accompanying drawings that form a part thereof, and in which is shown by way of illustration specific exemplary embodiments in which the disclosure may be practiced.

These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the disclosure. The following description is, therefore, merely exemplary.

Various embodiments provide an effective interference mitigation strategy in a satellite communication (SATCOM) system with cross-layer design.

Suppose there is a cognitive radio communication transmitter-receiver pair, operating in an open wireless environment where there could be intentional and unintentional RFI signals. The communication pair are separated with distance d_TR. The information bits at the transmitter are divided into frames. In each frame, there are L uncoded information bits and L₀ overhead bits. The information bits and overhead bits are encoded with a channel encoder with coding rate r. For a system with M-ary modulation scheme, the number of symbols in each frame is L_s=(L+L₀)/(r log₂ M), where L is chosen in a way such that L_s is an integer.

To avoid severe RFI, the transmitter and receiver employ a frequency hopping (FH) scheme. Suppose there are N channels for the cognitive communication pair to communicate.

For different types of RFI, there are 1≤n≤N sub-channels that could be interfered. Therefore, considering both intentional and unintentional interference, the received signal samples in discrete-time at receiver can be represented as

y _m=√{square root over (E_r)}h_m^(TR)x_m+√{square root over (E_I)}h_m^(1R)k_m+n_m, m=1,2, . . . , L_s

where E_r and E_I are the average received symbol energy from transmitter and synchronized aggregated RFI nodes respectively; x_m∈ S is the m-th modulated symbol at transmitter, with S being the modulation alphabet set with the cardinality M=|S|, k_m and z_m are the unknown synchronized interference and rest overall interference signal during the m-th symbol period, y_m, h_m^(TR), h_m^(IR), and n_m are the received sample, the fading coefficient between transmitter and receiver, the fading coefficient between the aggregated RFI node and receiver, and additive white Gaussian noise (AWGN) with single-sided power spectral density N₀=2σ², respectively. The z_m can be modeled as a Gaussian random variable with mean μ and variance 2α², which is quite flexible to model many weak interferes with varied μ and 2α² values. It is assumed that the transmitter and aggregated RFI node transmit each signal to receiver undergoes different path, therefore providing the independent path fading of h_m^(TR) and h_m^(IR).

To quantify the communication pair transmission effectiveness, spectral efficiency (SE) and energy efficiency (EE) are utilized as two metrics. The SE, η_SE is defined as the average data rate per unit bandwidth, which quantifies how efficient the precious spectrum is utilized to transmit information. The EE, η_EE, is defined as the successfully transmitted information bits per unit energy, which quantifies the average energy consumption to successfully transmit an information bit.

Based on the spectrum efficiency definition, the communication pair system SE can be represented as

${\eta }_{\mathrm{SE}}=\frac{R_d}{\left(1+\beta \right)R_s}$

where R_d is the net data rate of the successfully transmitted information bit, (1+β)R_s is the signal occupied bandwidth with β being the roll-off factor of the pulse shaping filter and R_s is the gross symbol rate. Note that in RF open wireless communications, each frame cannot be guaranteed to be transmitted successfully in one transmission attempt, because of the signal distortions caused by channel fading, intentional and unintentional interference, and noise, etc. Therefore, retransmissions must be incorporated to obtain the η_SE.

The probability that a frame can be successfully transmitted equals to 1-Φ, where Φ is the system outage probability which quantifies the frame transmission quality-of-services (QoS). Note that the communication system outage depends on many system parameters, including received signal-to-interference-plus-noise ratio (SINR), the transmission modulation and channel coding scheme, and the FH design, etc. For an automatic repeat request (ARQ) protocol, the average number of retransmissions is

$\Lambda =\frac{1}{1-\Phi }$

The system spectrum efficiency can then be calculated as

${\eta }_{\mathrm{SE}}=\frac{L}{L+L_0}\frac{{r\log }_2M}{1+\beta }\left(1-\Phi \right)$

Next, we derive the cognitive radio system energy efficiency in the condition of RFIs. Denote E_b as the average energy per uncoded information bit received at the receiver during one transmission attempt. The average SINR at the receiver is therefore

${\gamma }_b=\frac{E_b}{E_I+{\mu }^2+2{\alpha }^2+N_0}$

With a large-scale power path-loss model, the energy consumption for each symbol transmission at transmitter is

E _s =E _r G ₁ d _TK ^κ M _l

where κ is the path-loss exponent, G₁ is the gain factor at a unit distance including path-loss and antenna gain, and M_l is the link margin compensating the hardware process variations and other additive background noise and interference.

To derive a comprehensive energy efficiency of a communication system, the hardware energy consumption must be added to the information transmission energy consumption, which is positive proportional to the transmission energy consumption, which can be modeled as

$E_c=\left(\frac{{\xi }_M}{{\eta }_A}-1\right)E_s+\frac{\omega }{R_s}$

where η_A is the drain efficiency of the power amplifier, ξ_M is the peak-to-average power ratio (PAPR) of an M-ary modulation signal, and ω incorporates the effects of baseband processing at both transmitter and receiver, including signal processing, modulation and demodulation, channel encoding and decoding, etc, which can be treated as a constant in a frame with the designed transceiver structure.

The total energy consumption for the transmission of an information bit in one transmission attempt, E₀=(E_s+E_c)L_s/L can be represented as

$E_0=\frac{L+L_0}{L}\frac{{\gamma }_b{\xi }_MG_d\left(E_1+{\mu }^2+2{\alpha }^2+N_0\right)}{{\eta }_A}+\frac{\omega }{R_b}$

where G_d=G₁d_TR^κM_l and R_b=R_sL/L_s is the net bit rate of uncoded information bits.

Considering the frame retransmissions, the total required energy to successfully transmit an information bit from the transmitter to the receiver can then be obtained.

For the cognitive radio communication pair, it is desired to achieve both large SE and EE; however, the two metrics construct the fundamental trade-off in wireless communications. For a larger system SE, it is better for the transmitter to ensure the successful transmission probability of each frame by utilizing spectrum efficiently; which however requires more energy support, resulting in smaller EE, and vice versa.

Therefore, instead of maximizing either SE or EE, without considering the other one, we utilize a unified metric SEE (Spectral/Energy Efficiency) for a general trade-off configuration between SE and EE to fit for various scenarios and different system performances requirements. The SEE is defined as

η_SEE=η_SE^1−λ/E_t^λ

where λ is the weight represents the system preference of SE and EE, satisfying 0≤λ≤1. It can be seen that maximizing the SEE will increase η_SE or reduce energy consumption E_t, thus achieve a balanced trade-off between the SE and EE. Besides, the SEE is general and can be easily reduced to situations considering only the maximization of SE or EE for different system scenario requirements, i.e., λ can be set to 1 for a system considering only maximizing the EE for a device long working life time, and λ set to 0 for spectrum resource maximum utilization. With the derivation of η_SE and E_t, the η_SEE can then be obtained.

The unified metric η_SEE incorporates a number of system parameters, including SINR at the receiver, the number of information bits L in each frame, the information transmission modulation and channel coding scheme, and the system outage probability Φ which inherently depends on all the above parameters, with the weight coefficient λ to adjust preference weights between SE and EE.

It can be seen that the analysis of η_SEE relies on the system outage Φ expression,

Φ₀=f(γ=γ₀)

where γ₀ is the SINR threshold.

To obtain insights of interference impact to SATCOM communication pair for further adaptive configuration, |h_m^(TR)|² is set to 1 and χ₁=|h_m^(IR)|²≥0 is modeled with general Nakagami distribution, which is

$f\left({}_I\right)={\left(\frac{m_1}{{\stackrel{\_}{}}_I}\right)}^{m_1}\frac{{}_I^{m_1-1}}{\Gamma \left(m_1\right)}\exp \left(-m_1{}_I\right)d{}_I$

where m₁ is the channel fading shape factor and γ(·) is the incomplete gamma function. Note that the general Nakagami fading channel is flexible to model different channels, including AWGN, Rayleigh, and Rician fading channel.

The FH system outage can then be expressed as

${\Phi }_0=\frac{1}{\Gamma \left(m_1\right)}\Gamma \left(m_1,\frac{m_1P_r}{{\gamma }_0P_I}-\frac{m_1B}{P_I}\left({\mu }^2+2{\alpha }^2+N_0\right)\right)$

For a FH system, the center frequency of the communication pair varies with the assigned pseudo-random sequence, where the transmitted frequency can be seen as selected uniformly from the total frequency bandwidth W. Thus, RFI signals cannot always interfere the communication system, and FH scheme has shown to be an effective anti-RFI technique in severe hostile environment. The probability of a transmitted signal will be interfered is n/N.

Suppose the total signal transmission power and interference received power of aggregated RFI signals on the whole available bandwidth is P and P_J, respectively. The interference power on each channel for different types of RFI is then P_l=J₀B=P_J/n, where J₀ is the interference power spectral density.

Therefore, the average outage probability for a FH system with RFIs, is

${\Phi }_{}=\frac{n}{N\Gamma \left(m_1\right)}\Gamma \left(m_1,\frac{{\mathrm{nm}}_1P}{N{\gamma }_0P_JG_d}-\frac{{\mathrm{nm}}_1W}{{\mathrm{NP}}_J}\left(\Omega +N_0\right)\right)$

where Ω=|μ|²+2α².

Finally, the unified communication pair performance evaluation metric expression is

${\eta }_{\mathrm{SEE}}=\left[1-\frac{n}{N\Gamma \left(m_1\right)}\Gamma \left(m_1,\frac{{\mathrm{nm}}_1P}{N{\gamma }_0P_JG_d}-\frac{{\mathrm{nm}}_1R_b\left(1+\beta \right)\left(\Omega +N_0\right)}{{r\log }_2{\mathrm{MNP}}_J}\frac{L+L_0}{L}\right)\right]{{\left(\frac{L}{L+L_0}\frac{{r\log }_2M}{1+\beta }\right)}^{1-\lambda }\left[\frac{P{\xi }_M+{\eta }_A\omega }{R_B{\eta }_A}\right]}^{-\lambda }$

At the same time, a practical cognitive radio transceiver always has a power limit, satisfying 0<P≤P₀, where P₀ is the transmission power constraint.

The system optimum design for cognitive radio configuration, including power control P, information bits rate control R_b, the modulation scheme, and channel coding scheme, which can maximize the communication system unified SEE is discussed. Note that in many communication standards, the modulation schemes and channel coding schemes are often paired with each other to form a modulation and coding (MODCOD) combination table, such as in Digital Video Broadcasting-Satellite-Second Generation (DVB-S2) standard.

The optimization problem to a tuple (P, R_b,(M, r)) can be represented as

• • maximize η_SEE
  • subject to 0<P≤P₀, R_b>0,0<r<1, and M ∈ K⁺with η_SEE the developed general metric SEE and K refers to the set of all natural numbers.

Due to the high complexity representation and non-linearity of η_SEE, we transform the optimization metric to Ψ=log η_SEE. Note that because of the monotonically increasing function of η_SEE=exp(Ψ), the maximum Ψ gives the maximum η_SEE.

To solve the optimization problem, the constrained optimization is relaxed to the unconstrained problem, and by setting ∂Ψ/∂P=0 with ∂Ψ/∂R_b=0.

Power Selection (POWSEL): For a cognitive radio frequency hopping communication system in the RFI environment, the optimum transmission power P that maximizes the unified SE and EE is given by min [P′, P₀], where P′>0 is the solution of the following equation and P′+∞ when the following equation does not have solution.

$\frac{1}{1-\frac{n}{N}\frac{\Gamma \left(m_1,\frac{{\mathrm{nm}}_1P}{N{\gamma }_0P_JG_d}-\frac{{\mathrm{nm}}_1R_b\left(\Omega +N_0\right)}{{r\log }_2{\mathrm{MNP}}_JL_{\beta }}\right)}{\Gamma \left(m_1\right)}}\frac{n}{N\Gamma \left(m_1\right)}\exp \left(-\frac{{\mathrm{nm}}_1P}{N{\gamma }_0P_JG_d}+\frac{{\mathrm{nm}}_1R_b\left(\Omega +N_0\right)}{{r\log }_2{\mathrm{MNP}}_JL_{\beta }}\right){\left(\frac{{\mathrm{nm}}_1P}{N{\gamma }_0P_JG_d}-\frac{{\mathrm{nm}}_1R_b\left(\Omega +N_0\right)}{{r\log }_2{\mathrm{MNP}}_JL_{\beta }}\right)}^{m_1-1}\frac{{\mathrm{nm}}_1}{N{\gamma }_0P_JG_d}=\lambda \frac{{\xi }_M}{R_B{\eta }_A}$

Data Rate Selection (DRSEL): For a cognitive radio frequency hopping communication system in the RFI environment, the optimum information bits data rate R_b that maximizes the unified SE and EE is given by

$R_b=\frac{{r\log }_2{\mathrm{ML}}_{\beta }}{{\gamma }_0{\xi }_MG_d\left(\Omega +N_0\right)}\left(P{\xi }_M+{\eta }_A\omega \right)$

It can be seen that the closed-form solution of R_b is expressed as a function of the transmission power P, employed modulation scheme and channel coding scheme. Therefore, for a communication system with fixed values of above system parameters, the optimum value of information bits rate control can be directly calculated.

However, for a cognitive transmitter, which may has the capability to adjust all the above system parameters, where the joint optimization of transmission power P, information bits rate R_b, and MODCOD is required. To obtain the joint optimum values of tuple (P, R_b, (M, r)), the above two equations can be treated as two system equations of the parameters. However, due to the nonlinear functionality and high complexity to obtain the necessary conditions for (M,r), the optimum solution for tuple ({circumflex over (P)}, {circumflex over (R)}_b, ({circumflex over (M)}, {circumflex over (r)})) is not easy to be directly obtained. An effective iterative algorithm can then be developed to obtain the joint optimum values of P, R_b, and (M, r).

In FIG. 1, the system diagram for cross-layer SATCOM interference mitigation scheme has been depicted. Various traffic packets 101 includes audio, video, image, and text go through packet pre-processor 102 including deleting null packets and adding cyclic redundancy check (CRC). With baseband signaling 104 selected parameters from game theoretic engine, the frame slicer 103 forms a frame with varied data length and baseband signaling headers. The baseband signaling 104 includes selected modulation and channel coding (MODCOD), power control parameters, beamforming precoding indicator, and frequency hopping pattern. The forward error correction (FEC) 105 includes enhanced SATCOM channel coding scheme depicted in FIG. 2. The bit-to-symbol mapping 106 includes mapping bits to symbols based on the MODCOD. The frequency hopping (FH) 107 adjusts the transmitter frequency for different symbols based on the baseband signaling frequency hopping pattern. The beamforming 108 transmits the signal in the desired direction with baseband signaling precoding indicator and power control parameters. At the receiver, interference nulling 109 removes interferences from undesired direction with multiple antennas processing support. For single antenna, the notch filter can be applied for 109. In 110, frequency de-hopping is processed with synchronizations to transform radio frequency (RF) signal to baseband signal for further processing. In 111, the symbol demapping process symbols to bits for FEC decoding 112. After bits recovery, several statistic performance metrics are evaluated in 113 including bit error rate and frame error rate. With the evaluated epoch system performances and SATCOM situation awareness 114 information, game theoretic engine 115 is able to be executed for various traffic control methods for 101 and provide baseband signaling information for 104. The 114 situation awareness information includes channel signal-to-noise-and-interference (SINR) information in each carrier, interferences direction, and data traffic analysis and prediction.

In FIG. 2, the enhanced SATCOM channel coding scheme for interferences mitigation is depicted. The formed frame bitstream goes through a switch 201 which controls the encoding scheme outer code BCH coding 202 and turbo coding 203, in conjunction with the inner code 204. The switch is performed with baseband signaling MODCOD to deal with different interferences situation.

In FIG. 3, the BCH coding scheme is shown. For different BCH coding length 301, the decimal range for searching is firstly determined in 302. After obtaining the decimal range, the different decimal number is looped in 303. In 304, it looks up if the primitive polynomial vector is existed or not. In 305, it determines the summation of binary coefficient is even or not. In 306, the current coefficients are evaluated to see if the maximal linear-feedback shift register (LFSR) sequence can be provided. If yes, the current polynomials and its reciprocal polynomial are then recorded in 307. If the number in the range has all been looped in 308, the primitive polynomial vector is then outputted in 309, which is provided for BCH coding 310.

In FIG. 4, the cognitive radio joint power control, rate control, and MODCOD adaptive configuration in the physical layer is performed. With the input system parameters 401, the different MODCOD pair is looped in 402. The loop initial data rate and transmission power are set in 403. With POWSEL, the transmission power in the current loop is calculated in 404. The data rate is further calculated with DRSEL in 405. In 406, the data rate converges or not is determined. If yes, it goes to 407 where the unified spectrum and energy efficiency metric is outputted; otherwise, it goes to 404 for further transmission power calculation. In 408, it decides if the MODCOD are all traversed. If yes, the metric maximum value is picked up in 409, and the joint power control, data rate control, and MODCOD values are outputted in 410.

In the game model formulation, the aggregated effective data rate in each carrier is formed in the transmission pair side.

FIG. 5 depicts an exemplary cognitive radio testbed apparatus for implementing an exemplary anti-jamming method in a SATCOM system according to various disclosed embodiments. The exemplary cognitive radio testbed apparatus may be a hardware setup including DVB-S2 transmitters and receivers, where digital modulation M-ary phase shift keying (MPSK) modulation is used.

For example, the interferers may try to interrupt the data transmission from the transmitter to the receiver. A Universal Software Radio Peripheral (USRP) and Gnu's not Unix (GNU) Radio based hardware testbed apparatus has been implemented to demonstrate the integrated game theory enabled spectrum management and waveform adaptation. It is emulated that the interference and anti-interference conflicts in the frequency band of 1.3 GHz to 1.6 GHz.

When transmitting video stream or video data, interference and anti-interference experiments may be performed using the hardware-in-loop implementation setup as shown in FIG. 5. As a result, the adaptive configurations guided by the disclosed game strategies can maintain video streaming in the congested environment with inadvertent interferers.

As such, in addition to the game theoretic model for anti-jamming waveform adaptation, the present disclosure also provides a hardware-in-loop cognitive radio testbed apparatus used for implementing the disclosed anti-jamming method in a SATCOM system. An exemplary testbed apparatus includes the RF transmitter, the RF receiver, and jammers, each with Universal Software Radio Peripheral (USRP) and Gnu's not Unix (GNU) Radio to demonstrate the game theoretic anti-jamming capabilities via spectrum management and waveform adaptation. In embodiments, the hardware testbed apparatus may include a set of DVB-S2 transmitters and receivers.

While the disclosure has been illustrated with respect to one or more implementations, alterations and/or modifications can be made to the illustrated examples without departing from the spirit and scope of the appended claims. In addition, while a particular feature of the disclosure may have been disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular function. Furthermore, to the extent that the terms “including”, “includes”, “having”, “has”, “with”, or variants thereof are used in either the detailed description and the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.” The term “at least one of” is used to mean one or more of the listed items can be selected.

Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the disclosure are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in their respective testing measurements. Moreover, all ranges disclosed herein are to be understood to encompass any and all sub-ranges subsumed therein. For example, a range of “less than 10” can include any and all sub-ranges between (and including) the minimum value of zero and the maximum value of 10, that is, any and all sub-ranges having a minimum value of equal to or greater than zero and a maximum value of equal to or less than 10, e.g., 1 to 5. In certain cases, the numerical values as stated for the parameter can take on negative values. In this case, the example value of range stated as “less than 10” can assume values as defined earlier plus negative values, e.g. −1, −1.2, −1.89, −2, −2.5, −3, −10, −20, −30, etc.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims

1. A cross-layer design for anti-jamming scheme in a satellite communication (SATCOM) system, comprising: various traffic packet support, processing, and control for audio, video, image, and text data transmission;frame partitioning and formation for various traffic packets;forward error correction to encode bits for unintentional and intentional interferences mitigation;frequency hopping control for interferences avoidance;beamforming control to transmit the signal in desired directions;interference nulling to mitigate signals from undesired directions;synchronizations of radio frequency signal for baseband signal transformation and processing;performance measurement including frame error rate, system outage, spectrum efficiency, and energy efficiency;SATCOM situation awareness including SINR estimation, traffic analysis and prediction;interference model for system performance evaluation and planning;game theoretic engine for interactive entities action selection, prediction and SATCOM radio resource management;

2. The method according to claim 1, wherein anti-jamming capability is obtained: from the unified interference model, where both intentional interferences and unintentional interferences are considered and modeled;from the interference model where synchronized interferences are modeled as an aggregated node undergoes general Nakagami fading channel;from the interference model where unsynchronized interferences are modeled as AWGN with non-zero mean value.

3. The method according to claim 1, wherein anti-jamming capability is obtained: from unified system spectrum efficiency and energy efficiency metric;from the metric expression with various system parameters, including the length of information bit, data rate, power, modulation and channel coding sets, frequency hopping interference ratio, and channel fading;from the metric expression with system outage and automatic repeat request (ARQ) protocol for frequency hopping system.

4. The method according to claim 1, wherein anti-jamming capability is obtained: from two levels optimizations, including single side system optimizations and interactive entities social optimizations;from the single side system optimizations including data rate control, power control, and MODCOD selection;from the interactive entities game theoretic social optimizations including traffic control, MODCOD selection, frequency hopping pattern design, beamforming control, and interference nulling.

5. The method according to claim 4, wherein: in the single side optimization process, unified spectrum efficiency and energy efficiency is the optimization metric;the transmission power is obtained from POWSEL;the data rate control is obtained from DRSEL;the joint MODCOD selection, data rate control, and power control is obtained from FIG. 4 shown flowchart.

6. The method according to claim 4, wherein: in the game reasoning process, SATCOM transmission pair and jammers are included;multiple jammers are modeled as an aggregated intentional interference;SATCOM transmission pair is one player;aggregated intentional interference is another player.

7. The method according to claim 4, wherein information used in the game reasoning process is obtained: from a space object propagator, providing a location and a speed of a current satellite in the SATCOM system;from spectrum sensing, providing SINR estimation for all the carriers of the current satellite in the SATCOM system;from situational awareness, providing jammers localization;from traffic analysis, providing traffic prediction;from SATCOM performance evaluations, providing frame error rate, unified spectrum efficiency and energy efficiency, and aggregated effective data rate.

8. The method according to claim 4, wherein game reasoning model is obtained: with performance evaluation of frame error rate;with aggregated effective data rate in all channels;with frequency hopping incorporated;with information uncertainty incorporated.

9. The method according to claim 1, wherein: various traffic packets supported with audio, video, image, and text data;various traffic packets are configured by game theoretic engine with packet length and packet data rate;various traffic packets are formed as frames by frame partition with game theoretic engine configured MODCOD information.

10. The method according to claim 1, wherein: forward error correction code includes an outer code and an inner code;BCH and turbo codes serve as an outer code;BCH is encoded and decoded with designed primitive polynomial vector depicted in FIG. 3;LDPC codes serve as an inner code;a switch to adapt BCH and turbo code based on the configured MODCOD information.

11. The method according to claim 1, wherein: beamforming is formed for SATCOM signal transmission with game theoretic engine selected precoding matrix;interference nulling is formed for SATCOM signal reception for multiple antennas system, which degrades to a notch filter for single antenna system.

12. The method according to claim 1, wherein the game reasoning process is implemented by, the transmitter, the receiver, and multiple jammers, each including a Universal Software Radio Peripheral (USRP) configured with Gnu's not Unix (GNU) Radio;synchronization is performed with joint Costas loop, data-aided, and non-data-aided design.