Latent World Models enhance scene representation through temporal self-supervised learning, presenting a perception annotation-free paradigm for end-to-end autonomous driving. However, the reconstruction-oriented representation learning tangles perception with planning tasks, leading to suboptimal optimization for planning. To address this challenge, we propose WorldRFT, a planning-oriented latent world model framework that aligns scene representation learning with planning via a hierarchical planning decomposition and local-aware interactive refinement mechanism, augmented by reinforcement learning fine-tuning (RFT) to enhance safety-critical policy performance. Specifically, WorldRFT integrates a vision-geometry foundation model to improve 3D spatial awareness, employs hierarchical planning task decomposition to guide representation optimization, and utilizes local-aware iterative refinement to derive a planning-oriented driving policy. Furthermore, we introduce Group Relative Policy Optimization (GRPO), which applies trajectory Gaussianization and collision-aware rewards to fine-tune the driving policy, yielding systematic improvements in safety. WorldRFT achieves state-of-the-art (SOTA) performance on both open-loop nuScenes and closed-loop NavSim benchmarks. On nuScenes, it reduces collision rates by 83% (0.30% → 0.05%). On NavSim, using camera-only sensors input, it attains competitive performance with the LiDAR-based SOTA method DiffusionDrive (87.8 vs. 88.1 PDMS).

Over prolonged evolution, natural fish possess exceptional maneuverability. For underwater robotic fish, maneuverability is a crucial performance metric during locomotion. This paper proposes a turning control optimization framework for a multi-flexible-joint bionic robotic fish. Firstly, three distinct turning strategies are devised based on kinematic analysis of the flexible robotic fish’s turning motion. Experimental results indicate that the control strategies need to be adjusted with respect to motion frequency to achieve optimal performance for the flexible robotic fish. Furthermore, an optimization problem incorporating dynamic constraints and cost functions of the flexible robotic fish is constructed. Based on a Constrained Iterative Linear Quadratic Regulator (CILQR), a turning performance optimization method is designed. Subsequently, optimal control strategies under both stationary and motion states are derived, effectively enhancing the turning performance of the flexible robotic fish. Finally, simulation and experimental results validate the effectiveness of the designed method. The developed flexible robotic fish could achieve a maximum swimming speed of 1.63 BL/s (body lengths per second) and a maximum average turning speed of 130.5°/s, offering guidance for the practical application of flexible robotic fish in aquatic environments.

Due to the complex mechanism and fabrication process of flexible materials, it remains extremely challenging for a flexible robotic fish to achieve fast and efficient locomotion. In this article, taking advantage of the passive bending and energy storage properties of flexible materials, we propose an untethered robotic fish with multiple flexible joints to achieve high performance and low Cost of Transport (COT). First, combining rigid links and flexible materials, a compact flexible tail with a simple and efficient structure is proposed. Next, the pseudo-rigid body theory is applied to analyze the deformation of passive joints, and a full-state dynamic model is established. More importantly, an optimization method by adjusting the phase differences of the passive joints is used to obtain high aquatic performance. Finally, extensive simulations and experiments validate the effectiveness of the proposed method, and the robotic fish can achieve a maximum speed of 1.63 body length (BL) per second and a minimum COT of 4.8 J/m (2.87 J/m$\cdot$kg). Compared with the multi-joint robotic fish with a similar design, the COT is reduced by up to 81.05% with the basically same aquatic ability. Excitingly, the flexible robotic fish can achieve a COT of 7.36 J/m at 1.23 BL/s, which is 15.72%-36.34% lower than that of the bluefin tuna and is within the range of yellowfin tuna, offering valuable insight into high speed and long endurance applications for underwater robots.Note to Practitioners–This paper is motivated by the design and optimization of an efficient bionic flexible underwater robot with high aquatic abilities, which is conducive to aquatic tasks that require long-time and long-distance sailing, such as underwater topographic exploration, submarine archaeology, and underwater search and rescue. Existing studies of free-swimming bionic underwater robots usually focus on the improvement of swimming speed and rarely consider achieving both high swimming performance and low energy cost. Thus, this paper proposes a bionic underwater robot design with two joints made of flexible materials on the tail to address the problem. Based on detailed analyses of the hydrodynamic force and flexible joint deformation, we propose an effective optimization method for swimming performance. A series of simulations and experiments suggest that the mechatronic design and optimization method are practical and valid. Hopefully, our design and method can provide theoretical guidance for engineers to design and optimize robots with flexible joints.

Compared with rigid robots, soft robots have the advantages of inherent compliance, high adaptability, and impact tolerance. Many researchers are very interested in the motion design of soft robot underwater. In this paper, inspired by the method of octopus propulsion, a jet propulsion unit with 80% soft materials driven by pressure is designed. It can change the volume of its cavity to absorb and eject the fluid medium to make the robot move. According to the working characteristics of the jet unit, corresponding experiments are designed to analyze its force output, deformation, ejection flow, and pressure response characteristics. In order to expand the motion space of the robot, a buoyancy unit is designed to control the depth of the robot in the water. Three jet units and a buoyancy element are combined into a tetrahedron robot - jet soft robot (JSR). The feasibility of its motion is verified by experiments. Compared with other similar jet robots, the biggest feature of this robot is that the drive unit can bend or twist roughly along the centerline, which can prevent accidental collision and damage.

The high speed and low energy cost are two conflicting objectives in the motion optimization of bio-inspired underwater robots, but playing a very important role. To this end, this paper proposes an optimization strategy for swimming speed and power cost using an improved NSGA-II for a flexible robotic fish. A dynamic model involving flexible deformation is established for speed prediction with the hydrodynamic parameters identified. A back propagation (BP) neural network is applied to perform compensation of power cost prediction with the dynamic model's prediction as input. In particular, an NSGA-II-AMS method is developed to improve the efficiency of solving the two-objective optimization problem based on NSGA-II. Finally, extensive simulations and experimental results demonstrate the effectiveness of the proposed optimization strategy, which offers promising prospects for the flexible robotic fish performing aquatic tasks with different performance constraints.

Multilayer coded modulation (MLyC) in single-antenna and multiple-antenna wireless fading channels is investigated. While the MLyC has been known to achieve ergodic fading channel capacity, the problem of interest here is to design practical and efficient MLyC for nonergodic block-fading channels. We develop a design methodology which maximizes the information rate of MLyC, subject to an upper bound on the decoding error probability. Moreover, we show that the MLyC performs closer to channel capacity when the overall diversity order of the channel is higher and proper spatial interleaving is employed. The relationship between the MLyC scheme and other transmission techniques, such as multilevel coded modulation and bit-interleaved coded modulation (BICM), is also discussed. It is shown through simulation examples that in realistic block-fading channels, the MLyC with practical coded modulation outperforms the BICM without turbo receiver iteration. We propose the MLyC as a promising alternative to BICM, especially when turbo iterative processing is not desired, e.g., for progressive layered media transmission

In this paper we describe a general framework for the modelling of the TCP performance over MIMO wireless systems including parameters such as fading, space-time transmission schemes, multiple antenna size, modulation schemes, channel coding and ARQ. We apply the framework to analyze the performance, the optimal channel coding rate and the effect of Doppler on the TCP throughput over the BLAST MIMO system and the orthogonal space-time block coded (STBC) system. We use the network simulator ns-2 to demonstrate the accuracy of the proposed analytical framework in characterizing various parameters of the TCP performance. We apply our framework to study of the buffer occupancy for TCP over MIMO systems and to a system that does not follow the AIMD TCP principle: CBR video transmission over MIMO channels.

We propose a general framework based in the Gilbert model for cross-layer analysis of TCP and UDP over MIMO wireless systems. Our framework takes into consideration diverse system characteristics often difficult to express as a Gilbert model such as fading, space-time transmission schemes, modulation, channel coding and ARQ. We apply our framework to analyze the TCP performance of two representative MIMO systems, namely, the BLAST system and the orthogonal space-time block coded (STBC) system. In particular, we investigate the optimal information rate that maximizes the TCP throughput, the effect of Doppler on the optimal TCP throughput and the optimal channel coding rate for various modulations. We provide simulations results from the ns-2 network simulator to demonstrate the accuracy of the proposed analytical framework in characterizing the TCP performance. We further apply the framework to two additional cross-layer applications: the analysis of the buffer occupancy on the base station, and the analysis of CBR video transmission over MIMO systems. We show that while the optimal rate for maximum TCP throughput is far from the channel capacity, the optimal rate for error and delay-tolerant video transmission requires much higher rates, and so the physical layer should be aware and adapt to the type of application in order to increase the system performance. We also show that mobility benefits systems with larger buffers, especially for TCP, as the ARQ scheme is able to recover the shorter burst errors. In general, our investigation shows that the type of application plays a crucial role in the optimization of a wireless system, and that our modelling framework is useful for the cross-layer analysis and design of those systems.

In code-division multiple-access (CDMA) packet data networks, the throughput depends on physical-layer receiver algorithms and medium access control (MAC) layer protocols. Taking a holistic approach, we investigate the throughput of a CDMA network employing linear multiuser detection, type-I automatic retransmission request (ARQ), and packet combining. In particular, the following two models of CDMA data networks are considered. 1) Fixed-access CDMA data networks, by which we mean that the number of active users is fixed. The corresponding throughput is analyzed by using a one-dimensional Markov chain, and conditions for achieving the optimal throughput are explored. 2) Random-access CDMA data networks, in which we take into account the random arrivals/departures of users. By viewing the fixed-access network studied in the first case as a snapshot of the random-access network, we exploit the results therein to analyze the random-access network, under a processor-sharing system model. Moreover, we identify some important properties of the corresponding throughput and devise a simple recursive algorithm to find the throughput-optimal admission region. Some recent advances on large-system performance of various multiuser detection algorithms are employed in our study. The results in this paper quantitatively characterize the potential for network throughput gain by employing multiuser detection and packet combining, in both fixed-access and random-access CDMA packet data networks.

Abstract We consider dynamic channel management (DCM), more specifically power control and channel allocation, in multi‐carrier multi‐antenna wireless cellular systems. A quasi‐static channel model is assumed such that the channels remain approximately time‐invariant within each packet. On a packet‐by‐packet basis, the mobile station (MS) receivers feed back the DCM parameters to the corresponding base station (BS) transmitters in order to minimize the transmission power and strive to satisfy every individual user's data‐rate request. While optimum, centralized DCM for all active cells typically requires solution of a non‐convex optimization problem (which is subject to local minima) and requires intense channel feedback to a central controller. We instead consider sub‐optimal distributed DCM, where each individual cell locally optimizes its own performance based on the local channel information. In particular, we compare three distributed DCM schemes, namely the two‐dimensional DCM, which jointly adjusts both spatial and frequency sub‐channels of each BS–MS link, the one‐dimensional DCM, which adjusts only the frequency sub‐channels and the scalar DCM, which adjusts each BS–MS link by one scalar power coefficient. These DCM schemes are investigated in multi‐cell environments with realistic parameters; and it is seen that due to the multiple antennas, the maximum supportable rate (i.e. the rate supported by practically finite transmission power) is significantly increased, for example by a factor of two for users using four antennas and close to cell boundary. Copyright © 2004 John Wiley & Sons, Ltd.

The performance analysis and design optimization of low density parity check (LDPC) coded multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems for high speed wireless transmission is considered. The tool of density evolution with mixture Gaussian approximations is used to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system configurations which include different number of antennas, different channel models and different demodulation schemes; and the optimized performance is compared to the corresponding channel capacity.

The design of a blind receiver for coded orthogonal frequency-division multiplexing (OFDM) communication systems in the presence of frequency offset and frequency-selective fading is investigated. The proposed blind receiver iterates between a Bayesian demodulation stage and a maximum a posteriori (MAP) channel decoding stage; and the extrinsic a posteriori probabilities of data symbols are iteratively exchanged between these two stages to achieve successively improved performance. The Bayesian demodulator computes the a posteriori data symbol probabilities, based on the received signals (without knowing or explicitly estimating the frequency offset and the fading channel states), by using Markov chain Monte Carlo (MCMC) techniques. In particular, two MCMC methods, namely, the Metropolis-Hastings algorithm and the Gibbs sampler, are studied for this purpose. Computer simulation results show that the proposed Bayesian blind turbo receiver can achieve good performance and it is robust against modeling mismatch.

We consider a space-time coded (STC) orthogonal frequency-division multiplexing (OFDM) system with multiple transmitter and receiver antennas over correlated frequency- and time-selective fading channels. It is shown that the product of the time-selectivity order and the frequency-selectivity order is a key parameter to characterize the outage capacity of the correlated fading channel. It is also observed that STCs with large effective lengths and ideal built-in interleavers are more effective in exploiting the natural diversity in multiple-antenna correlated fading channels. We then propose a low-density parity-check (LDPC)-code-based STC-OFDM system. Compared with the conventional space-time trellis code (STTC), the LDPC-based STC can significantly improve the system performance by exploiting both the spatial diversity and the selective-fading diversity in wireless channels. Compared with the previously proposed turbo-code-based STC scheme, LDPC-based STC exhibits lower receiver complexity and more flexible scalability. We also consider receiver design for LDPC-based STC-OFDM systems in unknown fast fading channels and propose a novel turbo receiver employing a maximum a posteriori expectation-maximization (MAP-EM) demodulator and a soft LDPC decoder, which can significantly reduce the error floor in fast fading channels with a modest computational complexity. With such a turbo receiver, the proposed LDPC-based STC-OFDM system is a promising solution to highly efficient data transmission over selective-fading mobile wireless channels.

We consider the design of iterative receivers for space-time block-coded orthogonal frequency-division multiplexing (STBC-OFDM) systems in unknown wireless dispersive fading channels, with or without outer channel coding. First, we propose a maximum-likelihood (ML) receiver for STBC-OFDM systems based on the expectation-maximization (EM) algorithm. By assuming that the fading processes remain constant over the duration of one STBC code word and by exploiting the orthogonality property of the STBC as well as the OFDM modulation, we show that the EM-based receiver has a very low computational complexity and that the initialization of the EM receiver is based on the linear minimum mean square error (MMSE) channel estimate for both the pilot and the data transmission. Since the actual fading processes may vary within one STBC code word, we also analyze the effect of a modeling mismatch on the receiver performance and show both analytically and through simulations that the performance degradation due to such a mismatch is negligible for practical Doppler frequencies. We further propose a turbo receiver based on the maximum a posteriori-EM algorithm for STBC-OFDM systems with outer channel coding. Compared with the previous noniterative receiver employing a decision-directed linear channel estimator, the iterative receivers proposed here significantly improve the receiver performance and can approach the ML performance in typical wireless channels with very fast fading, at a reasonable computational complexity well suited for real-time implementations.

We consider the design of iterative receivers for space-time block coded orthogonal frequency-division multiplexing (STBC-OFDM) systems in unknown wireless dispersive fading channels, with or without outer channel coding. First, we propose a maximum-likelihood (ML) receiver for STBC-OFDM systems based on the expectation-maximization (EM) algorithm. By assuming that the fading processes remain constant over the duration of one STBC codeword, and by exploiting the orthogonality property of the STBC as well as the OFDM modulation, we show that the EM-based receiver has a very low computational complexity, and that the initialization of the EM receiver is based on the linear minimum mean-square-error (MMSE) channel estimate for both the pilot and the data transmission. Since the actual fading processes may vary within one STBC codeword, we also analyze the effect of a modelling mismatch on the receiver performance, and show both analytically and through simulations that the performance degradation due to such a mismatch,is negligible for practical Doppler frequencies. We further propose a turbo receiver based on the maximum a posteriori (MAP)-EM algorithm for STBC-OFDM systems with outer channel coding. Compared with the previous non-iterative receiver employing a decision-directed linear channel estimator, the iterative receivers proposed here significantly improve the receiver performance and can approach the ML performance in typical wireless channels with very fast fading, at a reasonable computational complexity well suited for real-time implementations.

We consider the design of a blind optimal multiuser receiver for space-time block coded (STBC) multi-carrier code-division multiple-access (MC-CDMA) systems in unknown frequency-selective fading channels. A novel blind Bayesian multiuser detector is derived for joint estimation of unknown fading channel and symbols. Such a detector is based on the Bayesian inference of all unknown quantities. The Gibbs sampler, a Markov chain Monte Carlo (MCMC) method, is then used for Bayesian computation. Moreover, being soft-input and soft-output, the proposed Bayesian multiuser detector fits well into the turbo receiver framework and it exchanges the extrinsic information with the MAP channel decoder to successively refine its performance. Finally, its performance over random generated slow and fast frequency-selective fading channel is demonstrated through simulation examples.

The design of a blind receiver for coded orthogonal frequency-division multiplexing communication systems in the presence of frequency offset and frequency-selective fading is investigated. The proposed blind receiver iterates between a Bayesian demodulation stage and a maximum a posteriori channel decoding stage. The extrinsic a posteriori probabilities of data symbols are iteratively exchanged between these two stages to achieve successively improved performance. The Bayesian demodulator computes the a posteriori data symbol probabilities, based on the received signals (without knowing or explicitly estimating the frequency offset and the fading channel states), by using Markov chain Monte Carlo (MCMC) techniques. In particular, two MCMC methods-the Metropolis-Hastings algorithm and the Gibbs sampler-are studied for this purpose. Computer simulation results show that the proposed Bayesian blind turbo receiver can achieve good performance and is robust against modeling mismatch.

We consider the design of optimal multiuser receivers for space-time block coded (STBC) multicarrier code-division multiple-access (MC-CDMA) systems in unknown frequency-selective fading channels. Under a Bayesian framework, the proposed multiuser receiver is based on the Gibbs sampler, a Markov chain Monte Carlo (MCMC) method for numerically computing the marginal a posteriori probabilities of different users' data symbols. By exploiting the orthogonality property of the STBC and the multicarrier modulation, the computational complexity of the receiver is significantly reduced. Furthermore, being a soft-input soft-output algorithm, the Bayesian Monte Carlo multiuser detector is capable of exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel code decoders of all users, and successively improving the overall receiver performance. Several practical issues, such as testing the convergence of the Gibbs sampler in fading channel applications, resolving the phase ambiguity as well as the antenna ambiguity, and adapting the proposed receiver to multirate MC-CDMA systems, are also discussed. Finally, the performance of the Bayesian Monte Carlo multiuser receiver is demonstrated through computer simulations.

We consider a space-time coded (STC) orthogonal frequency-division multiplexing (OFDM) system in frequency-selective fading channels. By analyzing the pairwise error probability (PEP), we show that STC-OFDM systems can potentially provide a diversity order as the product of the number of transmitter antennas, the number of receiver antennas and the frequency selectivity order, and that the large effective length and the ideal interleaving are two most important principles in designing STCs for OFDM systems. Following these principles, we propose a new class of trellis-structured STCs. Compared with the conventional space-time trellis codes, our proposed STC's significantly improve the performance by efficiently exploiting both the spatial diversity and the frequency-selective-fading diversity.

In this paper, by drawing analogies between a synchronous CDMA system and an STC multiuser system, we study the applications of some multiuser detection methods to STC multiuser systems. Specifically, we show that the so-called "turbo multiuser detection" technique, which performs soft interference cancellation and decoding iteratively, can be applied to STC multiuser systems in Rayleigh flat-fading channels. An iterative multiuser receiver are developed for both the space-time block coding (STBC) system and the space-time trellis coding (STCC) system. During iterations, extrinsic information computed and exchanged between a soft multiuser demodulator and a bank of MAP decoders, to achieve successively refined estimates of the users' signals. Computer simulations demonstrate that the proposed iterative receiver techniques provide significant performance improvement over conventional non-iterative methods in both single-user and multiuser STC systems. Furthermore, the performance of the proposed iterative multiuser receiver approaches that of the iterative single-user receiver in both STBC and STTC systems.

Space-time coding (STC) techniques, which combine antenna array signal processing and channel coding techniques, are very promising approaches to substantial capacity increase in wireless channels. Multiuser detection techniques are powerful signal processing methodologies for interference suppression in CDMA systems. In this paper, by drawing analogies between a synchronous CDMA system and an STC multiuser system, we study the applications of some multiuser detection methods to STC multiuser systems. Specifically, we show that the so-called "turbo multiuser detection" technique, which performs soft interference cancellation and decoding iteratively, can be applied to STC multiuser systems in flat-fading channels. An iterative multiuser receiver and its projection-based variants are developed for both the space-time block coding (STBC) system and the space-time trellis coding (STTC) system. During iterations, extrinsic information is computed and exchanged between a soft multiuser demodulator and a bank of MAP decoders, to achieve successively refined estimates of the users' signals. Computer simulations demonstrate that the proposed iterative receiver techniques provide significant performance improvement over conventional noniterative methods in both single-user and multiuser STC systems. Furthermore, the performance of the proposed iterative multiuser receiver approaches that of the iterative single-user receiver in both STBC and STTC systems.