Search Results (103)

Orthogonal Frequency Division Multiplexing (OFDM) modulation currently dominates the physical layer design in modern transmission systems. Its primary advantage is the simple reconstruction of channel frequency response (CFR). However, the Least Squares (LS) algorithm commonly used here is prone to significant estimation errors due to noise interference. A promising and relatively simple alternative is a DFT-based strategy that uses a pre-computed refinement/correction matrix to improve estimation performance. This paper investigates two implementation approaches for CFR reconstruction with pre-computed matrices. Focusing on multiplication operations, a threshold number of active subcarriers was identified at which these two implementations exhibit comparable numerical complexity. A numerical performance factor was defined and a detailed performance analysis was carried out for different guard interval (GI) lengths and the number of active subcarriers in the OFDM signal. Additionally, to maintain channel estimation quality irrespective of GI length, a channel impulse response (CIR) energy detection procedure was introduced. This procedure refines the results of the symbol synchronization process and, by using the circular shift property, preserves constant values of the precomputed matrix coefficients without system performance loss, as measured by Bit Error Rate (BER) and Mean Square Error (MSE) metrics. Full article

Orthogonal frequency division multiplexing (OFDM) has been regarded as an attractive waveform for integrated sensing and communication (ISAC). However, suffering from its high peak-to-average power ratio (PAPR), sensitivity to phase noise (PN), and spectral efficiency saturation, the performance of OFDM in ISAC is limited. Against this background, this paper proposes a constellation-optimized index-modulated OFDM (CO-IM-OFDM) framework that leverages neural networks to design a constellation suitable for subcarrier activation patterns. A correlation model between index modulation and constellation is established, enabling adaptive constellation mapping in IM-OFDM. Then, Adam optimizer is employed to train the constellation tailored for ISAC, enhancing spectral efficiency under PN and PAPR constraints. Furthermore, a weighting factor is defined to characterize the joint communication–sensing performance, thus optimizing the overall system performance. Simulation results demonstrate that the proposed method can achieve improvements in bit error rate (BER) by over 4 dB and in Cramér–Rao bound (CRB) by 2% to 8% compared to traditional IM-OFDM constellation mapping. It overcomes fixed constellation constraints of conventional IM-OFDM systems, offering theoretical innovation waveform design for low-power communication–sensing systems in highly dynamic environments. Full article

This paper proposes a new carrier domain approach to suppress spreading first-order sea clutter in shipborne passive radar systems using Digital Radio Mondiale (DRM) signals as illuminators. The DRM signal is a broadcast signal that operates in the high-frequency (HF) band and employs orthogonal frequency-division multiplexing (OFDM) modulation. In shipborne DRM-based passive radar, sea clutter sidelobes elevate the noise level of the clutter-plus-noise covariance matrix, thereby degrading the target signal-to-interference-plus-noise ratio (SINR) in traditional space–time adaptive processing (STAP). Moreover, the limited number of space–time snapshots in traditional STAP algorithms further degrades clutter suppression performance. By exploiting the multi-carrier characteristics of OFDM, this paper proposes a novel algorithm, termed Space Time Adaptive Processing by Carrier (STAP-C), to enhance clutter suppression performance. The proposed method improves the clutter suppression performance from two aspects. The first is removing the transmitted symbol information from the space–time snapshots, which significantly reduces the effect of the sea clutter sidelobes. The other is using the space–time snapshots obtained from all subcarriers, which substantially increases the number of available snapshots and thereby improves the clutter suppression performance. In addition, we combine the proposed algorithm with the dimensionality reduction algorithm to develop the Joint Domain Localized-Space Time Adaptive Processing by Carrier (JDL-STAP-C) algorithm. JDL-STAP-C algorithm transforms space–time data into the angle–Doppler domain for clutter suppression, which reduces the computational complexity. Simulation results show the effectiveness of the proposed algorithm in providing a high improvement factor (IF) and less computational time. Full article

The recent rapid deployment of low-Earth-orbit (LEO) broadband constellations has positioned these systems as expected emerging navigation sources, thereby driving research interest in integrated navigation and communication (INAC) technologies. Existing INAC waveforms face various challenges in LEO environments, including limited ranging accuracy due to high mutual interference (MI) between signal components, a heavy signal processing burden for navigation users, or degraded data transmission reliability. We propose an INAC waveform named delay–Doppler block division multiplexing (DDBDM) in this work. MI is effectively reduced by modulating pseudo-random noise (PRN) codes and data separately on orthogonal delay–Doppler (DD) blocks. Navigation and communication signals in DDBDM can be separated in the frequency band, which allows the user to receive only the bandwidth occupied by the navigation subcarriers, reducing the signal processing overhead. Moreover, data transmission in the DD domain exhibits a low bit error rate in high-mobility channels, which enables fast and reliable navigation augmentation information for users. Simulation results demonstrate that DDBDM offers superior navigation performance and data transmission reliability compared to existing INAC schemes. The proposed waveform enhances the performance of the LEO INAC system and effectively extends the position, navigation, and timing (PNT) service capability. Full article

This paper proposes a novel blind channel estimation method using convolutional neural network (CNN)-based resource grouping. The traditional K-means-based blind channel estimation scheme suffers limitations in reflecting fine-grained channel variations in both the time and frequency domains. To address these limitations, we propose dynamic resource grouping based on CNN architecture utilizing a two-step learning process that adapts to various channel conditions. The first step of the proposed method identifies the optimal number of subcarriers for each channel condition, providing a foundation for the second step. The second step adjusts the number of orthogonal frequency division multiplexing (OFDM) symbols, a parameter for determining the proposed pattern in the time domain, to adapt to dynamic channel variations. Simulation results demonstrate that the proposed CNN-based blind channel estimation method achieves high channel estimation accuracy across various signal-to-noise ratio (SNR) levels, attaining the highest accuracy of 82.5% at an SNR of 10 dB. Even when classification accuracy is relatively low, the CNN effectively mitigates signal distortion, delivering superior performance compared to conventional methods in terms of mean squared error (MSE) across diverse channel conditions. Notably, the proposed method maintains robust performance under high-mobility scenarios and severe channel variations. Full article

Digital terrestrial television is now implemented in many countries worldwide and is now mature. Digital Video Broadcasting-Terrestrial, second generation (DVB-T2) is the European standard adopted or deployed by European and African countries which uses Orthogonal Frequency-Division Multiplexing (OFDM) modulation to achieve good throughput performance. However, its main particularity is the number of subcarriers operated for OFDM modulation which varies from 1024 to 32,768 subcarriers. Also, mobile reception is planned in DVB-T2 in addition to rooftop antenna and portable receptions planned in DVB-T. However, the main challenge of DVB-T2 for mobile reception is the presence of a carrier frequency offset (CFO) which degrades the system performance by inducing an Intercarrier Interference (ICI) on the DVB-T2 signal. This paper evaluates the system performance in the presence of the CFO when Gaussian noise and a TU6 channel are applied. Universal Filtered Multicarrier (UFMC) and non-uniform constellations (NUCs) have previously demonstrated good performance in comparison with OFDM and Quadrature Amplitude Modulation (QAM) in DVB-T2. The impact of CFO on the UFMC- and NUC-based DVB-T2 system is additionally investigated in this work. The results demonstrate that the penalties induced by CFO insertion in UFMC- and NUC-based DVB-T2 are highly reduced in comparison to those for the native DVB-T2. At a bit error rate (BER) of ${10}^{-3}$, the CFO penalties induced by the native DVB-T2 are $0.96$$\mathrm{d}$$\mathrm{B}$ and 4 $\mathrm{d}$$\mathrm{B}$, respectively, when only Additive White Gaussian Noise (AWGN) is used and when TU6 is additionally considered. The penalties are equal to $0.84$$\mathrm{d}$$\mathrm{B}$ and $0.2$$\mathrm{d}$$\mathrm{B}$ for UFMC/NUC-based DVB-T2. Full article

Terahertz (THz) communication is a crucial technique in sixth generation (6G) mobile networks, which allow for ultra-wide bandwidths to enable ultra-high data rate wireless communication. However, the current subcarrier spacing and the size of fast Fourier transform (FFT) of the orthogonal frequency division multiplexing (OFDM) in 5G NR are insufficient regarding the bandwidth requirements of terahertz scenarios. In this paper, a novel waveform is proposed to address the ultra-wideband issue, namely the generalized filter bank orthogonal frequency division multiplexing (GFB-OFDM) waveform. The main advantages are summarized as follows: (1) The K-point IFFT is implemented by two levels of IFFTs in smaller sizes, i.e, performing M-point IFFT in N times and performing N-point IFFT in M times, where $K=N\times M$. (2) The proposed waveform can accommodate flexible subcarrier spacings and different numbers of the subbands to provide various services in a single GFB-OFDM symbol. (3) Different bandwidths can be supported using a fixed filter since the filtering is performed on each subband. In contrast, the cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) in 4G/5G requires various filters. (4) The existing detection for CP-OFDM can be directly employed as the detector of the proposed waveform. Lastly, the comprehensive simulation results demonstrate that GFB-OFDM outperforms CP-OFDM in terms of the out-of-band leakage, complexity and error performance. Full article

In this paper, we, for the first time, propose and demonstrate an orthogonal frequency division diversity and multiplexing (OFDDM) scheme for the sixth-generation (6G) underwater optical wireless communication (UOWC) systems. In OFDDM, the subcarriers are grouped into subblocks; the subcarriers within each subblock transmit the same constellation symbol through diversity transmission, while different subblocks transmit different constellation symbols via multiplexing transmission. As a result, OFDDM can support hybrid diversity and multiplexing transmission simultaneously. Moreover, the combination of subblock interleaving and low-complexity diversity is further proposed to efficiently mitigate the adverse low-pass effect and substantially reduce the computational complexity, respectively. The feasibility of OFDDM adapting to the various transmission conditions in UOWC systems has been verified via both simulations and experiments. Experimental results demonstrate that a striking 106.1% effective bandwidth extension can be obtained using OFDDM in comparison to conventional orthogonal frequency division multiplexing (OFDM) for a fixed spectral efficiency of 1 bit/s/Hz. Furthermore, OFDDM with adaptive bit loading can also gain a remarkable 13.3% capacity improvement compared with conventional OFDM with adaptive bit loading. Full article

Multicarrier navigation modulation is a trend within next-generation global navigation satellite systems (GNSS) aiming to enhance navigation performance, but it forces amplifiers to work in nonsaturation zones, resulting in low power efficiency. This paper presents constant-envelope multiplexing (CEM) based on clipping to overcome the low transmission efficiency of orthogonal multi-binary offset carriers (OMBOCs). The clip constant-envelope OMBOC (CCE-OMBOC) features a hard limit for the original OMBOC signal, and its cross-correlation function (CCF) has a fixed ratio with the CCF of the original OMBOC. Thus, the clipping process has no adverse effect on navigation performance. Additionally, the expression of transmission and multiplexing efficiency is presented according to OMBOC’s amplitude distribution. A low sampling rate is suggested for the CCE-OMBOC, which reduces the cost of signal generation. For OMBOC, the CCE-OMBOC provides multiplexing efficiency comparable to that of constant-envelope multiplexing via intermodulation construction (CEMIC). CCE-OMBOC has a straightforward generation process; in contrast, the complexity of CEMIC rises significantly with increasing subcarriers. Moreover, the CCE-OMBOC is a multicarrier CEM modulation tool that has good tracking performance and excellent compatibility. The greater the number of subcarriers, the more navigation services and the higher the navigation data rate. The CCE-OMBOC can be used in next-generation GNSS and integrated communication and navigation systems. Full article

To detect moving weak targets in the dual function radar communication (DFRC) system of an orthogonal frequency division multiplexing (OFDM) waveform, a modified hybrid integration method is addressed in this paper. A high-speed aircraft can cause range walk (RW) and Doppler walk (DW), rendering traditional detection methods ineffective. To overcome RW and DW, this paper proposes an integration approach combining DFRC and OFDM. The proposed approach consists of two primary components: intra-frame coherent integration and hybrid multi-inter-frame integration. After the echo signal is re-fragmented into multiple subfragments, the first step involves integrating energy across fixed situations within intra-frames for each subcarrier. Subsequently, coherent integration is performed across the subfragments, followed by the application of a Radon transform (RT) to generate frames based on the properties derived from the coherent integration output. This paper provides detailed expressions and analyses for various performance metrics of our proposed method, including the communication bit error ratio (BER), responses of coherent and non-coherent outputs, and probability of detection. Simulation results demonstrate the effectiveness of our strategy. Full article

In this article, a deep neural network (DNN)-based underwater acoustic (UA) communication receiver is proposed. Conventional orthogonal frequency-division multiplexing (OFDM) receivers perform channel estimation using linear interpolation. However, due to the significant delay spread in multipath UA channels, the frequency response often exhibits strong non-linearity between pilot subcarriers. Since the channel delay profile is generally unknown, this non-linearity cannot be modeled precisely. A neural network (NN)-based receiver effectively tackles this challenge by learning and compensating for the non-linearity through NN training. The performance of the DNN-based UA communication receiver was tested recently in river trials in Western Australia. The results obtained from the trials prove that the DNN-based receiver performs better than the conventional least-squares (LS) estimator-based receiver. This paper suggests that UA communication using DNN receivers holds great potential for revolutionizing underwater communication systems, enabling higher data rates, improved reliability, and enhanced adaptability to changing underwater conditions. Full article

An extremely large-scale antenna array (ELAA) can potentially provide significantly increased spatial multiplexing and beamforming gains, as well as enhanced localization capability. While presenting new potential, its near-field propagation and spatial non-stationary properties also impose a great challenge on the receiver design. This paper focuses on the receiver design in an uplink orthogonal frequency-division multiplexing system with a planar ELAA deployed at the base station. To solve the challenging problem of 3D user localization and channel estimation with the planar ELAA, a space-frequency user localization and channel reconstruction (SF-ULCR) receiver is proposed. Under the Bayesian framework, an extended probability model is first established, to capture the channel structural information comprehensively, based on which an iterative receiver consisting of three modules is derived: element-wise line spectrum estimation (ELSE), distance parameter estimation (DPE), and near-field localization (NFL). In particular, the ELSE module handles the line spectrum relationships among multiple subcarriers in the frequency domain, the DPE module extracts and integrates the distance information from the line spectrum parameters, and the NFL module utilizes the messages of distances for user localization based on near-field spatial characteristics. Our numerical results demonstrate that the proposed SF-ULCR algorithm outperforms existing baselines in terms of channel estimation and localization performance, and that it approaches the Cramèr–Rao bound. Full article

Addressing the challenges of high decoding latency, reduced spectral efficiency, and substantial storage requirements in a Cyclic Redundancy Check (CRC)Aided Successive Cancellation List (CA-SCL) polar decoder, this paper proposes a chaotic phase modulation direct-sequence spread spectrum (CPMDSSS)-assisted adaptive serial cancellation list decoding method for underwater acoustic communication. The method involves segmenting the information bits to be transmitted, computing CRC for each segment, and mapping all CRCs to a CPMDSSS, which is then modulated onto the pilot subcarriers of underwater acoustic orthogonal frequency-division multiplexing (OFDM) to increase spectral efficiency. At the receiving end, CRCs are obtained by demodulating the CPMDSSS to verify the segmented information and adaptively select the number of decoding paths. The theoretical analysis and simulation results demonstrate that compared to CA-SCL, the proposed method effectively reduces the required storage units and improves spectral efficiency, with an average reduction of approximately 80% in the decoding paths. Sea trials further indicate that the proposed method reduces the average decoding paths by approximately 71% and decreases the average decoding delay by approximately 64% compared to CA-SCL. Full article

Sixth-generation (6G) wireless networks demand a more efficient implementation of non-orthogonal multiple access (NOMA) schemes for severe multipath fading environments to serve multiple users. Using non-orthogonal multiple access (NOMA) schemes in IoT 6G networks is a promising solution to allow multiple users to share the same spectral and temporal resource, increasing spectral efficiency and improving the network’s capacity. In this work, we have evaluated the performance of a novel progressive pattern interleaver (PPI) employed to distinguish the users in interleaved division multiple access (IDMA) schemes, suggested by 3GPP guidelines as a NOMA scheme, with two multi-carrier modulation schemes known as single-carrier frequency-division multiple access (SC-FDMA) and orthogonal frequency-division multiplexing (OFDM), resulting in SC-FDMA-IDMA and OFDM-IDMA schemes. Both schemes are multi-carrier schemes with orthogonal sub-carriers to deal against inter-symbol interference (ISI) and orthogonal interleavers for the simultaneous access of multiple users. It has been suggested through simulation outcomes that PPI performance is adequate with SC-FDMA-IDMA and OFDM-IDMA schemes in terms of bit error rate (BER) under multipath channel conditions. Moreover, regarding bandwidth requirement and the implementation complexity of the transmitted interleaver structure, PPI is superior to the conventional random interleaver (RI). Full article

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) technology is widely used in integrated radar and communication systems (IRCSs). Moreover, index modulation (IM) is a reliable OFDM transmission scheme in the field of communication, which transmits information by arranging several distinguishable constellations. In this paper, we propose a sparse reconstruction-based joint signal processing scheme for integrated MIMO-OFDM-IM systems. Combining the advantages of MIMO and OFDM-IM technologies, the integrated MIMO-OFDM-IM signal design is realized through the reasonable allocation of bits and subcarriers, resulting in better intercarrier interference (ICI) resistance and a higher transmission efficiency. Taking advantage of the sparseness of OFDM-IM, an improved target parameter estimation method based on sparse signal reconstruction is explored to eliminate the influence of empty subcarriers on the matched filtering at the receiver side. In addition, an improved sequential Monte Carlo signal detection method is introduced to realize the efficient detection of communication signals. The simulation results show that the proposed integrated system is 5 dB lower in the peak sidelobe ratio (PSLR) and 1.5 ×${10}^5$ lower in the number of complex multiplications than the latest MIMO-OFDM system and can achieve almost the same parameter estimation performance. With the same spectral efficiency, it has a lower bit error rate (BER) than existing methods. Full article