Deep Learning for Over-the-Air Non-Orthogonal Signal Classification

Non-cooperative communications, where a receiver can automatically distinguish and classify transmitted signal formats prior to detection, are desirable for low-cost and low-latency systems. This work focuses on the deep learning enabled blind classification of multi-carrier signals covering their orthogonal and non-orthogonal varieties. We define two signal groups, in which Type-I includes signals with large feature diversity while Type-II has strong feature similarity. We evaluate time-domain and frequency-domain convolutional neural network (CNN) models in simulation with wireless channel/hardware impairments. Simulation results reveal that the time-domain neural network training is more efficient than its frequency-domain counterpart in terms of classification accuracy and computational complexity. In addition, the time-domain CNN models can classify Type-I signals with high accuracy but reduced performance in Type-II signals because of their high signal feature similarity. Experimental systems are designed and tested, using software defined radio (SDR) devices, operated for different signal formats to form full wireless communication links with line-of-sight and non-line-of-sight scenarios. Testing, using four different time-domain CNN models, showed the pre-trained CNN models to have limited efficiency and utility due to the mismatch between the analytical/simulation and practical/real-world environments. Transfer learning, which is an approach to fine-tune learnt signal features, is applied based on measured over-the-air time-domain signal samples. Experimental results indicate that transfer learning based CNN can efficiently distinguish different signal formats in both line-of-sight and non-line-of-sight scenarios with great accuracy improvement relative to the non-transfer-learning approaches

Non-Orthogonal Frequency Division Multiple Access

This paper proposes a frequency-domain multiple user access scheme termed non-orthogonal frequency division multiple access (NoFDMA), which maintains the same data rate per user while allowing more users to access via non-orthogonal user overlapping in a given spectral band. User side signal processing follows existing standards with minor modifications. Receiver side operation can jointly process signals from all the users. Computational complexity is investigated for NoFDMA, which shows slightly increased operations than the typical orthogonal frequency division multiple access (OFDMA). Nevertheless, effective spectral efficiency of NoFDMA, considering both raw spectral efficiency and computational complexity, is higher than that of OFDMA. The scalability of the multiple access scheme is flexible via tuning the user overlapping ratio. Simulation reveals that the number of accessed users is doubled using the NoFDMA strategy when compared with the traditional OFDMA scheme over the same spectral resource utilization

Real-Time Experimental Demonstration of Multi-band CAP Modulation in a VLC System with Off-the-Shelf LEDs

We demonstrate, for the first time, m-CAP modulation using off-the-shelf LEDs in a VLC in real time experimental setup using field programmable gate arrays based in universal software radio peripherals (USRPs). We demonstrate transmission speeds up to ~30 Mb/s can be achieved, which supports high definition television streaming.Comment: 2 pages, 4 figures, IEEE INFOCOM Demonstration

Design and Prototyping of Hybrid Analogue Digital Multiuser MIMO Beamforming for Non-Orthogonal Signals

To enable user diversity and multiplexing gains, a fully digital precoding multiple input multiple output (MIMO) architecture is typically applied. However, a large number of radio frequency (RF) chains make the system unrealistic to low-cost communications. Therefore, a practical three-stage hybrid analogue-digital precoding architecture, occupying fewer RF chains, is proposed aiming for a non-orthogonal IoT signal in low-cost multiuser MIMO systems. The non-orthogonal waveform can flexibly save spectral resources for massive devices connections or improve data rate without consuming extra spectral resources. The hybrid precoding is divided into three stages including analogue-domain, digital-domain and waveform-domain. A codebook based beam selection simplifies the analogue-domain beamforming via phase-only tuning. Digital-domain precoding can fine-tune the codebook shaped beam and resolve multiuser interference in terms of both signal amplitude and phase. In the end, the waveform-domain precoding manages the self-created inter carrier interference (ICI) of the non-orthogonal signal. This work designs over-the-air signal transmission experiments for fully digital and hybrid precoding systems on software defined radio (SDR) devices. Results reveal that waveform precoding accuracy can be enhanced by hybrid precoding. Compared to a transmitter with the same RF chain resources, hybrid precoding significantly outperforms fully digital precoding by up to 15.6 dB error vector magnitude (EVM) gain. A fully digital system with the same number of antennas clearly requires more RF chains and therefore is low power-, space- and cost- efficient. Therefore, the proposed three-stage hybrid precoding is a quite suitable solution to non-orthogonal IoT applications

Index Modulation Pattern Design for Non-Orthogonal Multicarrier Signal Waveforms

Spectral efficiency improvement is a key focus in most wireless communication systems and achieved by various means such as using large antenna arrays and/or advanced modulation schemes and signal formats. This work proposes to further improve spectral efficiency through combining non-orthogonal spectrally efficient frequency division multiplexing (SEFDM) systems with index modulation (IM), which can efficiently make use of the indices of activated subcarriers as communication information. Recent research has verified that IM may be used with SEFDM to alleviate inter-carrier interference (ICI) and improve error performance. This work proposes new SEFDM signal formats based on novel activation pattern designs, which limit the locations of activated subcarriers and enable a variable number of activated subcarriers in each SEFDM subblock. SEFDM-IM system designs are developed by jointly considering activation patterns, modulation schemes and signal waveform formats, with a set of solutions evaluated under different spectral efficiency scenarios. Detailed modelling of coded systems and simulation studies reveal that the proposed designs not only lead to better bit error rate (BER) but also lower peak-to-average power ratio (PAPR) and reduced computational complexity relative to other reported index-modulated systems

Partial OFDM Symbol Recovery to Improve Interfering Wireless Networks Operation in Collision Environments

The uplink data rate region for interfering transmissions in wireless networks has been characterised and proven, yet its underlying model assumes a complete temporal overlap. Practical unplanned networks, however, adopt packetized transmissions and eschew tight inter-network coordination, resulting in packet collisions that often partially overlap, but rarely ever completely overlap. In this work, we report a new design called (), that specifically targets the parts of data symbols that experience no interference during a packet collision. bootstraps a successive interference cancellation (SIC) like decoder from these strong signals, thus improving performance over techniques oblivious to such partial packet overlaps. We have implemented on the WARP software-defined radio platform and in trace-based simulation. Our performance evaluation presents experimental results from this implementation operating in a 12node software network testbed, spread over two rooms in a nonlineofsight indoor office environment. Experimental results confirm that our proposal decoder is capable of decoding up to 60 % of collided frames depending on the type of data and modulation used. This consistently leads to throughput enhancement over conventional WiFi under different scenarios and for the various data types tested, namely downlink bulk TCP, downlink videoondemand, and uplink UDP

Experimental SEFDM Pipelined Iterative Detection Architecture with Improved Throughput

In spectrally efficient frequency division multiplexing (SEFDM), the separation between subcarriers is reduced below the Nyquist criteria, enhancing bandwidth utilisation in comparison to orthogonal frequency division multiplexing (OFDM). This leads to self-induced inter-carrier interference (ICI) in the SEFDM signal, which requires more sophisticated detectors to retrieve the transmitted data. In previous work, iterative detectors (IDs) have been used to recover the SEFDM signal after processing a certain number of iterations, however, the sequential iterative process increases the processing time with the number of iterations, leading to throughput reduction. In this work, ID pipelining is designed and implemented in software defined radio (SDR) to reduce the overall system detection latency and improve the throughput. Thus, symbols are allocated into parallel IDs that have no waiting time as they are received. Our experimental findings show that throughput will improve linearly with the number of the paralleled ID elements, however, hardware complexity also increases linearly with the number of ID elements

A combined MMSE-ML detection for a spectrally efficient non orthogonal FDM signal

In this paper, we investigate the possibility of reliable and computationally efficient detection for spectrally efficient non-orthogonal Multiplexing (FDM) system, exhibiting varying levels of intercarrier interference. Optimum detection is based on the Maximum Likelihood (ML) principle. However, ML is impractical due to its computational complexity. On the other hand, linear detection techniques such as Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) exhibit poor performance. Consequently, we explore the combination of MMSE estimation with ML estimation around a neighborhood of the MMSE estimate. We evaluate the performance of the different schemes in Additive White Gaussian Noise (AWGN), with reference to the number of FDM carriers and their frequency separation. The combined MMSE-ML scheme achieves a near optimum error performance with polynomial complexity for a small number of BPSK FDM carriers. For QPSK modulation the performance of the proposed system improves for a large number of ML comparisons. In all cases, the detectability of the FDM signal is bounded by the signal dimension and the carriers frequency distance

An Experimental Proof of Concept for Integrated Sensing and Communications Waveform Design

The integration of sensing and communication (ISAC) functionalities have recently gained significant research interest as a hardware-, power-, spectrum- and cost- efficient solution. This experimental work focuses on a dual-functional radar sensing and communication framework where a single radiation waveform, either omnidirectional or directional, can realize both radar sensing and communication functions. We study a trade-off approach that can balance the performance of communications and radar sensing. We design an orthogonal frequency division multiplexing (OFDM) based multi-user multiple input multiple output (MIMO) software-defined radio (SDR) testbed to validate the dual-functional model. We carry out over-the-air experiments to investigate the optimal trade-off factor to balance the performance for both functions. On the radar performance, we measure the output beampatterns of our transmission to examine their similarity to simulation based beampatterns. On the communication side, we obtain bit error rate (BER) results from the testbed to show the communication performance using the dual-functional waveform. Our experiment reveals that the dual-functional approach can achieve comparable BER performance with pure communication-based solutions while maintaining fine radar beampatterns simultaneously