This paper presents an HLS-based algorithm-hardware co-design methodology and complete FPGA hardware accelerator for multi-user massive MIMO-OFDM receivers operating in contested tactical environments with jamming suppression capabilities. We develop a systematic bi-directional co-design methodology using high-level synthesis (HLS) where algorithms provide functional verification constraints while hardware synthesis feedback drives algorithmic complexity reduction, enabling efficient transformation from signal processing algorithms to optimized circuit implementations on the Xilinx ZCU111 radio frequency system-on-chip (RFSoC) platform. The primary contributions include: 1) hardware architecture innovations featuring QR decomposition-based synchronization achieving 330 MHz post-route operation and optimized frequency-domain minimum mean square error (FD-MMSE) equalization with systematic loop restructuring for data dependency removal in substitution modules, reducing hardware resources by 56% lookup tables (LUTs), 58% flip-flops (FFs), and 67% digital signal processing (DSP) blocks while maintaining real-time throughput; 2) systematic HLS-based co-design framework enabling automated architecture exploration with hardware-oriented algorithm adaptations including silent-period frame structure and Cholesky-based decision-feedback equalization; 3) complete system integration validated through field trials demonstrating 8 dB jamming suppression improvement with reliable spatial division multiple access (SDMA) communications. The presented methodology provides insights applicable to broader signal processing systems with stringent real-time constraints.

The paper considers monostatic ISAC transceivers relying on in-band full-duplex (IBFD) capability to achieve simultaneous sensing and communication. These systems transmit a waveform for both communication and sensing and receive target echoes and incoming communication signals from other nodes. The major challenge is interference cancellation, suppressing self-interference (SI) from the leaked transmitted signal and the mutual interference (MI) between the echo for sensing and incoming signals for communication. This paper proposes an advanced joint analog and two-stage digital interference cancellation (DIC) structure to address this challenge, enabling simultaneous communication and sensing in IBFD ISAC systems. The analog SI cancellation structure leverages an analog least mean square (ALMS) loop with specific design constraints to preserve the integrity of sensing signals. A track-and-hold mechanism is employed to avoid ALMS weighting coefficient variation caused by the strong reflected sensing signal and uplink communication signal. The novel two-stage DIC first cancels residual SI for sensing and then mitigates echo sensing signals for communication. Doppler effects in the echo signals are compensated during the second stage to ensure effective suppression of sensing signals and accurate retrieval of communication signals. Simulation results validate the proposed approach, showcasing its strong communication and sensing performance and robust interference cancellation capabilities.

This paper introduces a novel method for radio frequency (RF) self-interference (SI) cancellation in in-band full-duplex (IBFD) communication systems using a generalized analog least mean square (GALMS) loop. Conventional research in this area has predominantly focused on employing the tapped delay line (DL) structure to process the RF transmitted signal. The proposed GALMS loop utilizes a filter bank applied on the baseband transmitted signal to avoid the limitation of the conventional tapped DL adaptive filters, which require tapped spacing to satisfy the Nyquist principle. We utilize frequency domain representation and steady-state analysis to derive the modeling error and residual SI power of the proposed structure. Notably, the GALMS loop incorporating an allpass filter bank can achieve the same level of SI cancellation as the conventional DL structure with a significantly reduced number of taps. Simulations are conducted to validate the efficiency of the proposed GALMS loop and prove the theoretical findings.

For wideband transceivers operating at millimeter wave and terahertz frequencies, the implementation of conventional digital predistortion for nonlinearity mitigation faces significant challenges due to the limited availability and/or complexity of high-speed digital signal processing. In this paper, a simple received signal model is proposed for wideband system with nonlinearity and other practical impairments, such as transmitter (Tx) and receiver (Rx) I/Q imbalances (IQIs), carrier frequency offset (CFO), and phase noise, to enable low-complexity impairment mitigation. An expanded memory polynomial (EMP) model is firstly proposed to capture Tx IQI and the nonlinearity over the entire transceiver chain. Exploiting the CFO and a novel transmission protocol, a blind Rx IQI estimation is also proposed. The noise enhancement after Rx IQI and CFO compensation is then evaluated as a noise factor related to the mean-square-error of the Rx IQI estimation. As a result, the received signal of the wideband system is finally modelled as an EMP plus additive noises followed by a band-limited noisy receiver filter. Simulation results using a millimeter wave system with 2.5 GHz bandwidth and 73.5 GHz carrier frequency are presented to verify the accuracy of the EMP modelling and validate the theoretical analyses.

Wideband millimeter wave and terahertz systems face severe nonlinearity and other practical impairments such as transmitter and receiver in-phase/quadrature imbalances (IQIs), carrier frequency offset, and phase noise. Based on a simplified yet effective received signal model including an expanded memory polynomial (EMP) and a noisy receiver filter, this paper proposes a low-complexity digital post-cancellation (DPC) framework for transmitter IQI and overall system nonlinearity mitigation. The nonlinearity parameters with reduced nonlinearity order are firstly estimated with low-complexity using a novel transmission protocol incorporating both frame rotation and preamble power scaling. Through widely linear system equalization and interference cancellation, the signal distortion caused by frequency-dependent IQI and nonlinearity is then mitigated with significant performance improvement. The mean-squared-error measurement of the EMP-modelled signals also provides a practical means for the nonlinear system identification and characterization. Both simulation and experiment results obtained from a millimeter wave system with 2.125 GHz bandwidth and 73.5 GHz carrier frequency are presented to verify the theoretical analyses and demonstrate the effectiveness of the DPC technology.

An effective and practical joint analog and digital self-interference cancellation (SIC) scheme without additional signalling overhead for an I/Q imbalanced full duplex transceiver is proposed in this paper. This scheme combines an I/Q imbalanced analog least mean square (ALMS) loop at the transceiver radio frequency frontend and a two-stage digital signal processing (DSP) at the digital baseband to achieve excellent SIC performance with low complexity. The steady state weighting coefficients of the I/Q imbalanced ALMS loop with periodical transmitted signal and the loop’s convergence behaviour are firstly analysed. The residual SI is then modelled as the output of a time-varying widely linear system. With a track/hold control mechanism applied to the ALMS loop, the system model for digital SIC is further presented, followed by the DSP algorithms suitable for real-time implementation. The noise enhancement in each stage digital cancellation is also analysed and formulated. Finally, simulation results are provided to verify the theoretical analyses and demonstrate the overall SIC performance.

The performance of transmit beamforming for both optimized precoding and self-interference cancellation (SIC) in full duplex multiple input multiple output (MIMO) transceivers is analysed in this paper. With sub-space dimension larger than that of the null-space of the self-interference channels, the precoding error is reduced but the interference suppression ratio (ISR) is degraded, resulting in a trade-off between multibeam communication and MIMO SIC. An analytical approach for the ISR evaluation is proposed assuming known eigenvalue distribution of the self-interference channels, and a closed-form ISR expression is derived after applying a uniform distribution approximation. The ISR and precoding error trade-off curves are also formulated. Joint SIC by transmit beamforming and beam-based analog adaptive filters over both propagation and analog domains is proposed to achieve better SIC performance and enable more flexible receive antenna selection. Simulation results verify the theoretical analyses.

Joint analog and digital self-interference cancellation (SIC) is essential for enabling in-band full duplex (IBFD) communications. Analog least mean square (ALMS) loop is a promising low-complexity high-performance analog SIC technique with multi-tap adaptive filtering capability, but its properties on the tap coefficient variation have not been fully understood. In this paper, analysis based on higher-order statistics of the transmitted signal is performed to solve the problem of evaluating the variance of the ALMS loop’s weighting coefficient error, which reveals two additional types of irreducible residual self-interference (SI) produced by an ALMS loop if it runs freely. The residual SI channel impulse response in digital baseband is also analysed and its unique properties are investigated. By introducing a simple track and hold control to the ALMS loop’s tap coefficients, a joint analog and digital SIC scheme is proposed to stop the tap coefficient variation and achieve very low residual SI close to the IBFD receiver’s noise floor. In a coordinated application scenario, the noise figure of the digital SIC algorithm is proved to be only 1.76 dB at most. Simulation results are provided to verify the theoretical analyses.

Self-interference (SI) cancellation for full-duplex (FD) multiple input multiple output (MIMO) systems is challenging due to both hardware and signal processing complexity. In this paper, a beam-based adaptive filter structure with analog least mean square (ALMS) loops is proposed to significantly reduce the complexity of SI cancellation for FD MIMO systems. With this structure, the number of adaptive filters required for SI cancellation scales linearly with the number of transmit beams rather than quadratically with the number of antennas. Furthermore, to avoid additional transmit chains used to up-convert the beam signals to generate reference signals for the ALMS loops, a novel method is proposed to select the optimized reference signals from all transmitted signals. In addition, our stationary analysis shows that the proposed structure for FD MIMO systems outperforms the ALMS loop employed for an FD single input single output system. Simulations are conducted to confirm the theoretical analyses.

Analog least mean square (ALMS) loop is a promising method to cancel self-interference (SI) in in-band full-duplex (IBFD) systems. In this paper, the steady state analyses of the residual SI powers in both analog and digital domains are firstly derived. The eigenvalue decomposition is then utilized to investigate the frequency domain characteristics of the ALMS loop. Our frequency domain analyses prove that the ALMS loop has an effect of amplifying the frequency components of the residual SI at the edges of the signal spectrum in the analog domain. However, the matched filter in the receiver chain will reduce this effect, resulting in a significant improvement of the interference suppression ratio (ISR). It means that the SI will be significantly suppressed in the digital domain before information data detection. This paper also derives the lower bounds of ISRs given by the ALMS loop in both analog and digital domains. These lower bounds are joint effects of the loop gain, tap delay, number of taps, and transmitted signal properties. The discovered relationship among these parameters allows the flexibility in choosing appropriate parameters when designing the IBFD systems under given constraints.

Generalized continuous wave synthetic aperture radar (GCW-SAR) is a promising new imaging radar system since it applies the full-duplex (FD) transmission technique to achieve continuous signaling in order to overcome several fundamental limitations of the conventional pulsed SARs. As in any FD wireless communication system, self-interference (SI) is also a key problem which can impact on the GCW-SAR system. In this paper, the analog least mean square (ALMS) loop in the radio frequency domain is adopted to cancel the SI for a GCW-SAR system with periodic chirp signaling. The average residual SI power after the ALMS loop is analyzed theoretically by a stationary analysis. It is found that the ALMS loop not only works with random signals in general FD communication systems, but also works well with the periodic signal in GCW-SAR systems. Simulation results show that over 45 dB SI cancellation can be achieved by the ALMS loop which ensures the proper operation of the GCW-SAR system.

This paper evaluates the performance of an analog least mean square (ALMS) loop employed to cancel self-interference in in-band full-duplex (IBFD) orthogonal frequency division multiplexing (OFDM) systems. Cyclostationary analysis is applied to investigate the behavior of the ALMS filter. It is revealed that the performance of the ALMS filter for OFDM systems primarily depends on windowing function rather than pulse shaping as in single carrier systems. It is also noticed that the ALMS loop in OFDM systems provides a much higher level of sel-interference (SI) suppression because OFDM signals lead to reduced the error of the interference channel modelling with the adaptive filter. Simulations are then conducted to verify the theoretical findings.