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Different from terrestrial internet of things (IoT) applications, marine IoT applications need to solve the problem of information interaction between surface network and underwater network.The key to solve this problem is to design a proper routing scheme.An ad hoc on-demand distance vector for acoustic-radio integrated network (AR-AODV) was proposed based on location information and energy balance.The protocol enables surface radio links to forward more information data, so as to reduce the burden of underwater communication network and improve the overall performance.In the proposed protocol, the forwarding priority of the buoy nodes was higher than that of the underwater nodes.When the source node needs to send data, it enters the route discovery phase, i.e., the node uses its position and energy information as the heuristic information to calculate the forwarding probability and broadcast route request (RREQ) packets.When the destination node receives an RREQ packet, it sent an RREP packet to update the pheromone and select the optimal path based on the pheromone.Compared with AODV protocol, AR-AODV protocol has significantly improved the performance in terms of transmission success rate, transmission delay, throughput, energy conversion rate and routing packet forwarding times.

A space–air–ground–sea integrated network (SAGSIN) is a promising heterogeneous network framework for the next generation mobile communications. Moreover, federated learning (FL), as a widely used distributed intelligence approach, can improve advanced network performance. In view of the combination and cooperation of SAGSINs and FL, an FL-based SAGSIN framework faces a number of unprecedented challenges, not only from the communication aspect but also on the security and privacy side. Motivated by these observations, in this article, we first give a detailed state-of-the-art review of recent progress and ongoing research works on FL-based SAGSINs. Then, the challenges of FL-based SAGSINs are discussed. After that, for different service demands, basic applications are introduced with their benefits and functions. In addition, two case studies are proposed, in order to improve SAGSINs’ communication efficiency under a significant communication latency difference and to protect user-level privacy for SAGSIN participants, respectively. Simulation results show the effectiveness of the proposed algorithms. Moreover, future trends of FL-based SAGSINs are discussed.

Underwater Acoustic Channels (UAC) have inherent sparse characteristics. The traditional adaptive equalization techniques do not utilize this feature to improve the performance. In this paper we consider the Variable Adaptive Subgradient Projection (V-ASPM) method to derive a new sparse equalization algorithm based on the Minimum Symbol Error Rate (MSER) criterion. Compared with the original MSER algorithm, our proposed scheme adds sparse matrix to the iterative formula, which can assign independent step-sizes to the equalizer taps. How to obtain such proper sparse matrix is also analyzed. On this basis, the selection scheme of the sparse matrix is obtained by combining the variable step-sizes and equalizer sparsity measure. We call the new algorithm Sparse-Control Proportional-MSER (SC-PMSER) equalizer. Finally, the proposed SC-PMSER equalizer is embedded into a turbo receiver, which perform turbo decoding, Digital Phase-Locked Loop (DPLL), time-reversal receiving and multi-reception diversity. Simulation and real-field experimental results show that the proposed algorithm has better performance in convergence speed and Bit Error Rate (BER).

Abstract Multiple-mode orthogonal frequency division multiplexing with index modulation (MM-OFDM-IM) is a promising multiple-carrier modulation technique, which activates all OFDM subcarriers to transmit multiple distinguishable modes (or signal constellations, alternatively) and carries additional information with the full permutation of the modes, enjoying superior error performance and high spectral efficiency. In this paper, we propose a novel detector tailored to MM-OFDM-IM based on the expectation maximization (EM) algorithm to further improve the detection performance. The idea is to first select the signal constellation points candidates for any given mode permutation by applying the EM algorithm and then determine the most-likely mode permutation as well as the associated signal constellation points by minimizing the Euclidean distance. The effectiveness of the EM detector has been verified in terms of bit error rate (BER) performance by Monte Carlo simulations.

Underwater wireless communication technology plays a key role in the field of marine equipment technology. In this paper, we experimentally demonstrate an underwater optical–acoustic cooperative communication platform for an underwater wireless data transmission system. The system utilizes an underwater Remote-Operated Vehicle (ROV) as a carrier, equipped with LEDbased optical communication and acoustic communication modems. In particular, the system applies optical communication to transmit large-scale data and applies acoustic communication to provide acoustic-assisted signaling exchange before optical transmission and Automatic Repeat Request (ARQ) during optical transmission. By experimentally measuring the transmission distance under different water quality conditions, we found that the system can achieve a data rate of up to 5 Mb/s over a laboratory underwater channel of 7.6 m. By comparing the attenuation coefficients for the outdoor underwater environment with that in clear seawater, we estimate that the achievable link distance in clear seawater can reach 11 m with a data rate of 3.125 MB/s. The proposed system takes both implementation complexity and cost into consideration and also provides significant guidance for future real-time high-speed underwater optical–acoustic communications.

The transmissions of ocean information have to cross the water-air interface.In this case,the information transmission network architecture requires the efficient integration of the underwater acoustic network and the radio network.However,the performance of the underwater acoustic link lags far behind the radio link,and becomes a bottleneck that restricts the performance of marine information networks.An acoustic-radio cooperative marine information network was proposed,which exploited the cooperation of acoustic and radio links to improve network performance.After demonstrating the advantages of acoustic-radio cooperation through three application scenarios,the network architecture and protocols,as well as the challenges for the acoustic-radio cooperative maritime information network were discussed.Acoustic-radio cooperation was not only an effective method for realizing the integration of air-water networks,but also an important method for realizing the integration of network communications,computing,and storage in marine information networks.

In this paper we propose a new type of receiver for underwater acoustic communication. The proposed receiver has the following features: 1) It has a turbo structure with an embedded adaptive decision feedback equalizer (DFE), which is based on the least-symbols-error-rate criterion and is shown to outperform the conventional minimum mean square error (MMSE) equalizers; 2) By exploiting the training symbol at the beginning and at the end of a data frame, the proposed receiver employs time-reversal equalization to suppress the error propagation of the applied DFE, where the time-reversal diversity gain is exploited by combing the output of the bidirectional DFE with an equal-gain combing scheme; and 3) A receiving array is applied, where the output of each hydrophone is individually equalized and then the equalizer outputs are combined with an equal-gain combing scheme. The proposed receiver is extensively evaluated through computer simulation and field experiments, and is also compared with the conventional MMSE based receiver in terms of the bit error rate performance.

Multiple-input multiple-output orthogonal frequency division multiplexing with index modulation (MIMO-OFDM-IM) is a relatively new multicarrier transmission technique for the MIMO systems to achieve both energy and spectral efficiency. However, due to the dependence of subcarrier symbols introduced by the index modulation, existing MIMO detection techniques cannot be applied in MIMO-OFDM-IM as it will lead to erroneous detection on index information of the active subcarriers and further deteriorate the system performance. In this paper, we first develop an optimal detection algorithm with reduced complexity for MIMO-OFDM-IM by performing the subcarrier-wise detection under the constraint on the legal subcarrier combination within each OFDM-IM subblock. To further reduce the computational complexity, we then propose a low-complexity subcarrier-wise algorithm based on the deterministic sequential Monte Carlo technique to achieve near-optimal detection for MIMO-OFDM-IM. Specifically, the near-optimal detector applies the QR decomposition to generate an upper triangular structure and draw antenna-wise samples at the subcarrier level. Computational simulations and complexity analysis show that the proposed algorithms provide similar performance to optimal one with reduced computational complexity.

In conventional orthogonal frequency division multiplexing with index modulation (OFDM-IM), the M-ary modulated symbols are transmitted on a subset of subcarriers under the guidance of information bits. In this paper, a novel information guided precoding technique, called precoding aided (P-) OFDM-IM, is proposed to improve the spectral efficiency (SE) of OFDM-IM. In P-OFDM-IM, the information bits are jointly conveyed through the conventional M-ary modulated symbols and the indices of precoding matrices and vectors. The P-OFDM-IM principle is embodied in two different implementations, P-OFDM-IM-I and P-OFDM-IM-II. Specifically, P-OFDM-IM-I divides all subcarriers into L groups and modulates them using L distinguishable constellations. P-OFDM-IM-II partitions the set of all subcarriers into L overlapping layers and performs IM layer by layer, where distinguishable constellations are employed across layers. A practical precoding strategy is designed for P-OFDM-IM under the phase shift keying/quadrature amplitude modulation constraint. A low-complexity log-likelihood ratio detector is proposed to ease the computational burden on the receiver. To evaluate the performance of P-OFDM-IM analytically, an upper bound on the bit error rate and the achievable rate is studied. Computer simulation results show that P-OFDM-IM-I outperforms the existing OFDM-IM-related schemes at high SE, while P-OFDM-IM-II performs the best at low SE.

Adaptive linear equalizer, whose coefficients are designed to be adjustable to the channel impulse response, has emerged as a simple and efficient technique to adaptively compensate for the channel fading. However, conventional adaptive linear equalizers suffer from performance degradation and slow convergence in the underwater acoustic channel with large delay spread. To solve this problem, in this paper, we propose a novel adaptive decision-feedback equalizer (DFE) based on the minimum symbol-error rate (MSER) criterion. Specifically, by taking the sample-by-sample adaptation into account, the problem is first formulated as minimizing the norm between two consecutive adaptations under the constraint that the latest adaptation will provide correct detection for both the current and past symbols. Then we solve the optimization problem by using the Lagrange multiplier method to obtain the adaptive DFE that minimizes the sequential symbol detection error with a fast convergence rate. Simulation results show that the proposed MSER-based adaptive DFE significantly outperforms the existing equalizers in terms of convergence speed and steady-state performance for underwater acoustic channels.

Orthogonal frequency-division multiplexing with index modulation (OFDM-IM) has attracted much attention in recent years. In OFDM-IM, the information bits of a block are generally divided into several subblocks, each of which is further split into two parts, i.e., the index bits and the symbol bits. By performing a coordinate interleaving operation over each two constellation symbols, the bit-error-rate (BER) performance of the symbol bits is significantly improved in an existing OFDM-IM scheme, which is called coordinate-interleaved OFDM-IM (CI-OFDM-IM). In this paper, we propose a novel OFDM-IM scheme termed enhanced CI-OFDM-IM (ECI-OFDM-IM). In ECI-OFDM-IM, to improve the BER performance of the index bits, we adopt a special subcarrier-activation pattern (SAP) lookup table in which the Hamming distance of any pair of SAPs is at least four. To improve the BER performance of the symbol bits conveyed by the active subcarriers, the operations of rotating and coordinate interleaving are conducted twice over each four constellation symbols. Based on the maximum likelihood (ML) detection, a theoretical upper bound on the average bit-error probability of ECI-OFDM-IM is derived in closed form. By using the log-likelihood ratio method for SAP detection, a semi-ML detection scheme is proposed. Both the theoretical and simulation results show that ECI-OFDM-IM outperforms CI-OFDM-IM with additional diversity gains over frequency-selective Rayleigh fading channels.

In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB) of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.

This study presents a novel preamble-based timing offset estimation method for orthogonal frequency division multiplexing (OFDM) systems. The proposed method is robust, immune to the carrier frequency offset (CFO), and independent of the structure of the preamble. The performance of the new method is demonstrated in terms of mean square error (MSE) obtained by simulation in multipath fading channels. The results indicate that the new method significantly improves timing performance in comparison with existing methods.

In this paper, the estimation of overspread, i.e., doubly spread underwater acoustic (UWA) channels of strong dispersion is considered. We show that although the UWA channel dispersion causes the degeneration of channel sparsity, it leads to a low-rank structure especially when the channel delay-Doppler-spread function is separable in delay and Doppler domain. Therefore, we introduce the low-rank criterion to estimate the UWA channels, which can help to improve the estimation performance in the case of strong dispersion. The estimator is based on the discrete delay-Doppler-spread function representation of channel, and is formulated as a low-rank matrix recovery problem which can be solved by the singular value projection technique. Simulation examples are carried out to demonstrate the effectiveness of the proposed low-rank-based channel estimator.

The long propagation delay in underwater acoustic channels has attracted tremendous attentions in designing Medium Access Control (MAC). The low acoustic propagation speed and wide area of the acoustic communication range led to a wide range of variations in the propagation delay. This paper identifies an important characteristic of two-scale delay variations by field test results. We carry out simulations to study the impact of delay variations on MAC, and the results suggest a slot length adaptation scheme for the handshake and slotting based MAC. We further model an absorbing Markov chain to derive the closed-form equation for the throughput of MAC with adaptive slot length. Both the analytical and simulation results show that our proposed slot length adaptation improves significantly the throughput of MAC in underwater acoustic networks. Particularly, the Slotted-FAMA with an adaptive slot length achieves more than double the throughput than the Slotted-FAMA with a fixed slot length in a network with six nodes.

A joint blind order-detection and parameter-estimation algorithm for a single-input multiple-output (SIMO) channel is presented. Based on the subspace decomposition of the channel output, an objective function including channel order and channel parameters is proposed. The problem is resolved by using a specifically designed genetic algorithm (GA). In the proposed GA, we encode both the channel order and parameters into a single chromosome, so they can be estimated simultaneously. Novel GA operators and convergence criteria are used to guarantee correct and high convergence speed. Simulation results show that the proposed GA achieves satisfactory convergence speed and performance.