This demo introduces WaveBox, a dynamic, software-defined waveform generation system developed to assess the resilience of communication networks against many types of interference scenarios. WaveBox features seamless waveform switching, allowing users to efficiently adjust interference patterns to adapt to diverse operational scenarios. We will showcase the system's effectiveness and versatility, highlighting its ability to adapt to evolving mission requirements. Additionally, the system's intuitive graphical user interface (GUI) supports rapid waveform adjustments, enhancing its responsiveness in dynamic environments. WaveBox can provide a flexible software-defined tool for evaluating the robustness of wireless systems.

We design and implement a new multiple-input multiple-output (MIMO) frequency-division-duplex (FDD) spread-spectrum link and demonstrate real-time high-definition (HD) video streaming over a Radio Frequency System-on-a-Chip (RFSoC) software-radio testbed. To the best of our knowledge, this is the first-of-its-kind high-throughput low-latency full-duplex spread-spectrum link on RFSoC platforms which demonstrates an aggregated data throughput of 122 Mbps that supports real-time recording and playback of uncompressed full-HD video. The testbed comprises two Xilinx Zynq Ultrascale+ RFSoC ZCU111 evaluation kits with a custom-built application layer. A host-based graphical user interface (GUI) demonstrates live performance of the proposed 4×4 MIMO wireless link in terms of error vector magnitudepre-detection SINR and bit error rate (BER) and enables on-the-fly reconfiguration of link parameters such as spreading code sequence, transmit/receive antenna gains.

In highly dynamic and contested RF environments, communication systems must swiftly adapt to fluctuating spectral conditions while ensuring network quality of service (QoS). Maintaining link synchronization and spectral efficiency during waveform adaptation is particularly challenging due to the high mobility and autonomy of devices, coupled with the possibility of operating in GPS-denied environments. In this demo, we introduce a scalable, high-speed FPGA-based parallel decoding algorithm that leverages the HORNets signature adaptation protocol to address these challenges. Our solution preserves link synchronization within a multi-node network and enables efficient, lightweight waveform adaptation without reliance on GPS. The algorithm's resilience and effectiveness are demonstrated using a three-node cluster configuration, all subjected to non-colored or colored intentional interference.

We consider the problem of interference avoidance in orthogonal frequency-division multiplexing (OFDM) communication systems. Unlike conventional OFDM systems that rely on static waveform designs, we propose to apply a coding sequence at the input of the inverse discrete Fourier transform (IDFT) operator to digitally shape the transmitted OFDM waveform. By dynamically optimizing the coding sequence to maximize the signal-to-interference-plus-noise ratio (SINR) at the receiver, the proposed approach enables resilient communication in heavily congested spectral environments in a technically simple and efficient manner. We carry out extensive simulation studies to evaluate the performance of the proposed system under various interference scenarios and demonstrate significant improvements in SINR when compared to conventional OFDM systems. When the proposed dynamic OFDM waveform optimization process is fielded in commercially available software-defined radio platforms, the transceiver can evade rapidly changing (msec–scale or faster) interference and survive in contested spectral environments.

In this study, the authors investigate the information theoretical limits on the performance of single‐carrier cooperative underwater acoustic communication systems in the presence of intersymbol interference. The authors assume decode‐and‐forward relaying and consider orthogonal half‐duplex cooperation. Under the assumptions of sparse and frequency‐selective Rician fading channel and non‐white correlated Gaussian ambient noise, the authors derive expressions for bounds on the individual and achievable rates for both cases where channel state information is available at the transmitter or not. Using these expressions, the authors optimise input signalling and relay location to maximise average achievable rates.

Although there has been a growing interest on the study of diversity-multiplexing tradeoff (DMT), the existing works are mostly restricted to the outcomes reported for Rayleigh, Rician, and Nakagami fading channels. In this paper, we investigate the optimal tradeoff in the presence of log-normal fading, which provides an accurate model for indoor wireless, optical wireless, and ultra-wideband channels. We consider a multiple-input multiple-output (MIMO) log-normal channel, derive the outage probability expression, and then present the asymptotical DMT expression. It is shown that the asymptotical maximum diversity gain tends to infinity with logarithm of signal-to-noise ratio (SNR). To have further insight, we normalize the DMT with that of single-input single-output case and express the relative asymptotical DMT of the MIMO log-normal channel as a function of the number of transmit and receive antennas. We further study DMT for finite SNRs and demonstrate convergence to the asymptotical case. Extensive numerical results are provided to corroborate the analytical derivation.

In this study, the authors investigate the information theoretical limits on the performance of point‐to‐point single‐carrier acoustic systems over frequency‐selective underwater channels with intersymbol interference. Under the assumptions of sparse and frequency‐selective Rician fading channel and non‐white correlated Gaussian ambient noise, the authors derive an expression for channel capacity and demonstrate the dependency on channel parameters such as the number, location and power delay profile of significant taps, as well as environmental parameters such as distance, temperature, salinity, pressure and depth. Then, the authors use this expression to determine the optimal carrier frequency, input signalling and bandwidth for capacity maximisation.