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In this paper, we investigate the realization of synchronized spread spectrum code division multiple access (synchronized SS-CDMA) for the quasi-zenith satellite system (QZSS) safety confirmation system during major disasters. The QZSS is expected to provide a highly accurate positioning service and allow two-way communication, which includes the terminal location and short messages. The proposed synchronized SS-CDMA scheme realizes direct access from mobile terminals to the satellite and the simultaneous transmission of many users using SS codes with a large spreading factor. All terminals synchronize their own clock and frequency with those of the global navigation satellite system (GNSS). In this scheme, maintaining orthogonality among users in both the time and frequency domains is the most important problem. In this paper, for the consideration of mobile use, the effect of residual timing jitter and frequency offset in a fading environment is evaluated by computer simulation. As a result, acceptable timing and frequency errors for terminals are clarified in order for the system to be viable using the GNSS. [ABSTRACT FROM AUTHOR]

This paper proposes a new reentry trajectory generation method, which mainly comprises two parts: reentry profile design and trajectory optimization. Different from conventional methods that design angle-of-attack (AOA) and bank-angle profiles, a height-range profile is proposed in this paper. Using this profile, the AOA can be directly derived and the quasi-equilibrium glide condition is easily satisfied. In addition, the bank angle is analytically derived with the heading error, with only one reversal. Finally, the original problem is transformed into a parameter optimization problem and solved by an improved particle swarm optimization (PSO) method. In PSO, a comparison principle is proposed to tackle constraints and three modifications are applied to the swarm evolution to enhance the searching capacity. To conquer disturbances, an online profile updating strategy is developed based on the nominal profile, so complicated work of designing a trajectory tracker is avoided. Simulation validates the effectiveness of the proposed method and demonstrates that the improved PSO is comparable to the pseudospectral method and is better than the basic PSO. [ABSTRACT FROM AUTHOR]

Vehicle platooning systems are often equipped with vehicle-to-vehicle (V2V) communication technologies to improve both the road efficiency and road safety by exchanging vehicle information over wireless networks to maintain relatively small inter-vehicle distance. The road safety often relies on the quality of service delivered by the V2V communication. The V2V networks are, however, subject to channel fading and often have limited communication bandwidth. The limited bandwidth inevitably compromises the road safety as the vehicular network will easily get congested if the number of vehicles joining the network increases. To address the challenges of ensuring vehicle safety under unreliable wireless network with limited bandwidth, this paper first uses a two-state Markov chain to model the channel fading in vehicular networks. Under the Markov chain model, this paper further develops a novel distributed event triggered strategies under which the vehicle platooning system achieves stochastic $\mathcal {L}_2$ string stability while ensuring an efficient use of the limited communication bandwidth. The simulation results are provided to verify the effectiveness and advantages of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper proposes an application of a new electric motor topology named ring-winding axial flux machine (AFM) for rim-driven thruster of ship propulsion system. Ring-winding AFM has many advantages, such as reliability, simple construction, ease of increasing phase numbers, and pole numbers, which are important for marine application. In rim-driven thruster, the electric motor is fitted in the duct surrounding propeller so that electric motor and propeller are integrated into one unit. Due to this integration, the electric motor design is more affected by the design of propeller and hull. This paper presents a new method to determine electric motor specifications considering propeller and hull. Design methodology and constraints are presented for the ring-winding AFM as well. To prove the concept of the proposed topology, confirm manufacturability, and substantiate validity of three-dimensional (3-D) FEM simulations, a small-scale prototype is fabricated and tested. Furthermore, to demonstrate the effectiveness of the proposed method for determining electric motor specifications, a case study is done for Nordhavn 52 ship. Then, a ring-winding AFM is designed and its performance is evaluated with 3-D FEM simulations. [ABSTRACT FROM AUTHOR]

This paper studies and analyzes the performance of the licensed-assisted access (LAA) scheme introduced by 3GPP in LTE Release 13, and adopted by 3GPP in LTE Release 14, which is called 3GPP LAA scheme for short. Considering the characteristics that the 3GPP LAA scheme is different from other LAA schemes and IEEE 802.11 distributed coordination function (DCF) protocol in WiFi systems, the 3GPP LAA scheme is modeled as a new two-dimensional discrete Markov model, and the collision probability and the channel occupancy utilization are further derived based on the proposed model. To more deeply analyze the performance of the 3GPP LAA scheme by comparisons, we also derive the expressions of the same performance indices for the linear backoff based LAA scheme proposed in this paper and the fixed contention window based LAA scheme mentioned in existing literatures. The simulation and numerical results prove the validity of the proposed Markov chain model, and also show that the 3GPP LAA scheme is the friendliest one to WiFi networks among the three LAA schemes, whereas its total channel occupancy utilization is the lowest when the number of LAA small base stations (SBSs) is little and that is the highest when large. However, the other two LAA schemes are still the graceful coexistence, which is defined as the scheme where the interference to WiFi users caused by LAA SBSs coexisting with them is not more than that caused by other WiFi APs replacing the LAA SBSs. [ABSTRACT FROM AUTHOR]

In multi-user multiple-input multiple-output (MIMO) systems, a base station requires downlink channel state information for each user to suppress interferences. In time-varying environments, however, channels at the actual transmission time differ from the estimated ones because we have delay. This causes interference and deteriorates the packet error rate performance. To overcome this problem, we previously proposed a channel prediction method based on direction of arrival (DOA) estimation of multipath components obtained with a compressed sensing technique. This method can predict channels with high accuracy when we can assume that user equipment alone moves and the surrounding scatterers are stationary. In real environments, however, this assumption does not hold, and this method cannot be applied. In this paper, we propose a prediction method using two-step compressed sensing without the above assumption. In the first step, we estimate the DOAs of multipath signals. In the second step, we estimate the Doppler frequencies and their complex amplitudes using the estimated DOA information. From these values, we predict the MIMO channels at the actual transmission time. We discuss the performance of this method in this paper. [ABSTRACT FROM AUTHOR]

A ticket dispenser (TD) is used to assist customers with the waiting process in, e.g., a restaurant. This paper deploys a mobile TD system (MTDS) with waiting time prediction to enhance the user experience while waiting. For example, the MTDS for a restaurant allows a customer to remotely draw a ticket for a meal order anywhere through a smartphone before she/he arrives at the restaurant and therefore reduces her/his waiting time. The developed MTDS system can dynamically adjust the predicted waiting time. We propose two output indicators and develop a discrete-event simulation model to investigate the performance of the predicted time adjustment (PTA) mechanism for the MTDS. With a proper frequency of recalculation for the predicted waiting times, this paper indicates that the waiting times can be more accurately predicted without consuming more wireless network resources and power of mobile devices. [ABSTRACT FROM PUBLISHER]

This paper proposes a framework to construct 3-D complementary codes (3DCCs), which enable chip-level space–time coding to integrate multiantenna and multiple-access techniques in a unified platform. The 3DCCs are generated based on an extension method with the help of traditional complementary codes and well-designed matrices. The relationship between the correlation properties and flock size of the constructed 3DCCs is analyzed, and the proposed framework provides a generic way to construct different families of 3DCCs with a controllable tradeoff between their correlation properties and flock sizes. As examples, three families of 3DCCs with different characteristic features are constructed using the framework, and their correlation properties are simulated to validate their properties. The general architecture of the 3DCC-based multiple-input multiple-output (MIMO) system is also proposed in this paper. The simulated bit-error-rate (BER) performance of the corresponding system over both flat and multipath fading channels show that the constructed 3DCCs can eliminate both multiuser and multipath interferences in multiuser MIMO communications. The property to provide both transmit diversity and multiplexing with its uniquely flexible tradeoff between the two also makes it particularly well suited for futuristic wireless communications to fit to varying channel conditions and application requirements. [ABSTRACT FROM PUBLISHER]

In orthogonal frequency-division multiplexing (OFDM)-based cognitive radio (CR) systems, power optimization algorithms have been evaluated to maximize the achievable data rates of the secondary user (SU). However, unrealistic assumptions are made in the existing work, i.e., a Gaussian input distribution and traditional interference model that assumes a frequency-division multiplexing modulated primary user (PU) with perfect synchronization between the PU and the SU. In this paper, we first derive a practical interference model by assuming OFDM modulated PU with imperfect synchronization. Based on the new interference model, the power optimization problem is proposed for the finite symbol alphabet (FSA) input distribution [i.e., $M$-ary quadrature amplitude modulation (M-QAM)] , as used in practical systems. The proposed scheme is shown to save transmit power and to achieve higher data rates compared with the Gaussian optimized power allocation and the uniform power loading schemes. Furthermore, a theoretical framework is established in this paper to estimate the power saving by evaluating optimal power allocation for the Gaussian and the FSA input. Our theoretical analysis is verified by simulations and is proven to be accurate. It provides guidance for the system design and gives deeper insights into the choice of parameters affecting power saving and rate improvement. [ABSTRACT FROM PUBLISHER]

Battery energy is always limited in most wireless networked nodes, but wireless power transfer has the potential to address the problem for good. In this paper, we study the problem of collaborative charging decisions in Wireless Rechargeable Sensor Networks (WRSNs). In these networks, multiple Wireless Charging Vehicles (WCVs) need to decide which of the requesting sensors to charge and in what order. Our approach is to convert the decision makers, i.e., WCVs, into game players for higher profit. With the use of Nash Equilibrium, our newly designed scheme, named Game Theoretical Collaborative Charging Scheduling (GTCCS), enables WCVs to make optimal charging decisions. Besides, the result of the game is Pareto-optimal by carefully designing the rules of this game. We introduce the game theory model in this paper and explain how it is played by WCVs, with the goal of increasing overall energy usage efficiency. Extensive simulations and lab/field experiments show that GTCCS is able to achieve a much higher energy usage efficiency and lower the number of dead nodes. The dynamic characteristics of the GTCCS scheme also allow us to introduce the two unique features to further improve system performance, i.e., dynamic warning threshold for WCVs and sacrifice-charge. [ABSTRACT FROM AUTHOR]

The 21st century is defined as the era of technological development. With drastic increase in population, automation is becoming the need of the hour in order to make life more comfortable and easy. Due to the advancement and development in the field of automation and embedded system, the notion of smart car has become very popular. Smart cars are modernizing trends in the traditional automobile industry. Companies across the globe have been investing a huge amount of resources on the production and design of smart cars. Every technological development needs to overcome certain obstacles, and hence, in this paper, a design of a collision detection system for smart car using light fidelity (Li-Fi) and ultrasonic sensor on the Arduino platform is proposed. This design consists of an ultrasonic sensor, an Arduino processor, and a Li-Fi circuit. The ultrasonic is used for measurement of distance between vehicles, and Arduino processes the data and makes decisions accordingly. Data transmission between vehicles is ensued using a Li-Fi transmitter circuit and a Li-Fi receiver circuit. The transmitter circuit is mounted on the tail lights of the leading car and the receiver circuit is mounted on the front side of the car that follows. Using visible light communication, the transmitter circuit transmits the calculated speed and the information is received by the receiver circuit of the second car. On the basis of the information received, the speed of the second car is changed in order to avoid collision. In this paper, a system that can detect and thus avoid collision between vehicles and prevent accidents is proposed and studied. [ABSTRACT FROM AUTHOR]

The electric vehicle battery life is generally affected by its rapid utilization, accumulated heat and overall energy throughput. Inclusion of ultracapacitor along with battery provides enhanced flexibility in operating and utilizing the battery more adequately. In such dual storage systems, the energy management scheme plays an important role in determining the overall system efficiency. In this paper, a new concept to manage the state of charge (SOC) of ultracapacitor is proposed. The aim of the proposed approach is, based on the vehicle velocity at acceleration, to regulate the amount of energy that ultracapacitor should support in order to ensure its availability for an extended period. A two-stage artificial neural network based strategy is developed to achieve the aforementioned ultracapacitor SOC control. The battery energy throughput and its temperature rise during a complete battery discharge are taken as key parameters for the evaluation. It is shown in the paper that with the proposed approach, the energy storage system efficiency and battery life can be improved significantly. Finally, the applicability of the proposed concept is demonstrated experimentally. [ABSTRACT FROM AUTHOR]

Vehicle-to-vehicle (V2V) communication based on the device-to-device (D2D) communication in long term evolution (LTE) system is emerging as a key enabler for connected vehicles today. In this paper, we consider safety-related messages periodically transmitted by vehicle to announce its current status to other neighboring vehicles. The current state-of-the-art LTE V2V communication uses greedy algorithm for the transmission of such periodic messages. Greedy algorithm is known to have decent performance, but the performance is limited due to the lack of a collision–detection mechanism. In this paper, we proposefeedback-aided greedy algorithm (FAGA)to complement the drawback of greedy algorithm. We evaluate FAGA via realistic simulations to show that it outperforms comparison schemes in terms of overall message reception ratio (MRR). As a result, it is shown that FAGA operates well even with small amount of feedback and its performance is close to the performance of centralized scheduling method. Moreover, FAGA outperforms greedy algorithm by up to 23.7% in terms of MRR performance. [ABSTRACT FROM AUTHOR]

Energy efficiency aspects in cellular networks can contribute significantly to reducing worldwide greenhouse gas emissions. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Moreover, introducing renewable energy as an alternative power source has become a real challenge among network operators. In this paper, we formulate an optimization problem that aims to maximize the profit of Long-Term Evolution (LTE) cellular operators and to simultaneously minimize the \CO2 emissions in green wireless cellular networks without affecting the desired quality of service (QoS). The BS sleeping strategy lends itself to an interesting implementation using several heuristic approaches, such as the genetic (GA) and particle swarm optimization (PSO) algorithms. In this paper, we propose GA-based and PSO-based methods that reduce the energy consumption of BSs by not only shutting down underutilized BSs but by optimizing the amounts of energy procured from different retailers (renewable energy and electricity retailers), as well. A comparison with another previously proposed algorithm is also carried out to evaluate the performance and the computational complexity of the employed methods. [ABSTRACT FROM AUTHOR]

This paper discusses interference precancellation in digital hierarchical broadcasting (HB). In particular, we present the principles and implementation of structured dirty paper coding (SDPC) that approaches the capacity limit of dirty paper coding in multilayer broadcasting. As an alternative to Tomlinson-Harashima precoding (THP), SDPC eliminates the significant performance loss suffered by THP in the low signal-to-noise ratio (SNR) regime due to :he modulo operation. The key idea behind the SDPC scheme is the exploitation of the modulation structure of interference, thereby simplifying the demodulation process in hierarchical reception. We exemplify the SDPC technique by implementing an SDPC-based HB system on a real-time test bed. The experimental results show that SDPC delivers the performance of "superposition coding with successive interference cancellation" without extra computation or memory requirements at the receiver side. [ABSTRACT FROM AUTHOR]

A compact and efficient design for the electromagnetic interference (EMI) filter stage has become one of the most critical challenges in designing a high-density power converter, particularly for avionic applications. To maintain the regulatory standard requirements, EMI filter design needs to be precisely implemented. However, the attenuation characteristics of common-mode (CM) and differential-mode (DM) EMI filters may vary in practice from their respective theoretical calculations due to difficulty and inaccuracy in the noise modeling. This is particularly true for a three-phase active boost rectifier, which inherently has a CM high-frequency component in the rectifier output. This paper puts forward a detailed mathematical modeling of CM noise, originated from different sources, and discusses a concept to significantly reduce the CM noise effects. Furthermore, minimizing the weight and size of DM filter stage has been a design concern as the DM stage consumes a significant part of the weight of the whole system. This paper proposes a compact EMI filter topology with enhanced power density, which aims at satisfying the conducted EMI requirements according to DO-160F in avionics applications. The experimental verifications of the designed EMI filter are performed from the conducted emission results, obtained from a 6-kW laboratory prototype of an integrated stage of EMI and three-phase boost PFC converter. [ABSTRACT FROM AUTHOR]

We consider the problem of multiantenna source detection with dimension reduction in distributed wireless networks. Traditional strategies typically collect and perform raw data at the fusion center. In moderate-to-large-scale networks, however, the schemes create the bottleneck of computation and communication for high-dimensional data. The goal of this paper is to design a distributed algorithm in multiple-antenna wireless networks to project the raw data into the low-dimensional data to reduce the communication and computation burden while maintaining high detection performance. In this paper, a pseudosketching matrix is constructed to transform the raw data of each multiple-antenna node into the low-dimensional data. Furthermore, it is transformed into the vector by using the subspace method. By gathering the data vectors of all nodes at the fusion center, the eigenvalue-based detection methods, such as the generalized likelihood ratio test (GLRT), can be applied directly to determine if the source signal exists or not. Moreover, using the concentration inequalities of subgamma random variables, the theoretical analysis is derived to support the claim that the proposed algorithm has high detection performance. The simulations are presented to demonstrate the effectiveness of our proposed algorithm. [ABSTRACT FROM AUTHOR]

Spectrum sensing is a prominent functionality to enable dynamic spectrum access (DSA) in cognitive radio (CR) networks. It provides protection to primary users (PUs) from interference and creates opportunities of spectrum access for secondary users (SUs). It should be performed efficiently to reduce the number of false alarms and missed detections. Continuous sensing for a long time incurs cost in terms of increased energy consumption; thus, spectrum sensing ought to be energy efficient to ensure the prolonged existence of CR devices. This paper focuses on using of history to help achieve energy-efficient spectrum sensing in infrastructure-based CR networks. The scheme employs an iteratively developed history processing database that is used by CRs to make decisions about spectrum sensing, subsequently resulting in reduced spectrum scanning and improved energy efficiency. Two conventional spectrum sensing schemes, i.e., energy detection (ED) and cyclostationary feature detection (CFD), are enriched by history to demonstrate the effectiveness of the proposed scheme. System-level simulations are performed to investigate the sensitivity of the proposed history-based scheme by performing detailed energy consumption analysis for the aforementioned schemes. Results demonstrate that the employment of history ensued in improved energy efficiency due to reduced spectrum scanning. This paper also suggests which spectrum sensing scheme can be the best candidate in a particular scenario by looking into computational complexity before comparative analysis is presented with other states of the art. [ABSTRACT FROM PUBLISHER]

Reliability is of fundamental importance for the performance of secondary networks in cognitive radio networks (CRNs). To date, most studies have focused on predicting reliability parameters based on prior statistics of traffic patterns from user behavior. In this paper, we define a few reliability metrics for channel access in multichannel CRNs that are analogous to the concepts of reliability and availability in classical dependability theory. Continuous-time Markov chains are employed to model channel available and unavailable time intervals based on channel occupancy status. The impact on user access opportunities based on channel availability is investigated by analyzing the steady-state channel availability and several system times such as mean channel available time and mean time to first channel unavailability. Moreover, the complementary cumulative distribution function for channel availability is derived by applying the uniformization method, and it is evaluated as a measure of guaranteed availability for channel access by secondary users. The precision and the correctness of the derived analytical models are validated through discrete-event-based simulations. We believe that the reliability metric definitions and the analytical models proposed in this paper have their significance for reliability and availability analysis in CRNs. [ABSTRACT FROM PUBLISHER]

This paper presents how the time-differenced carrier phase (TDCP) can be implemented in nondifferential global positioning system/inertial measurement unit (GPS/IMU) tightly coupled navigation systems to improve positioning performance. The TDCP is expressed as a conventional TDCP, representing the carrier phase difference between two successive GPS epochs, and a modified TDCP, which is defined in this paper as the carrier phase difference between current and reference GPS epochs. Both of these two TDCP expressions are implemented in a GPS/IMU tightly coupled navigation Kalman filter as observations: The conventional TDCP with a more accurate approximation of the velocity integration is applied to estimate velocity, whereas the modified TDCP is used for position estimation. When initialized with a high-accuracy reference position, the proposed navigation strategy can achieve submeter positioning accuracy in the nondifferential mode without estimating ambiguities. Compared with the conventional TDCP-only method, the inherent position drift problem of the TDCP observations can also be avoided. The absolute positioning accuracy of the proposed conventional+modified TDCP measurement update method is determined by the reference position, since the TDCP, including conventional and modified TDCP, is a relative measurement. However, even when initialized with a low-accuracy reference position, the relative positioning accuracy (or precision) of the proposed method is still very high, and the reference positioning accuracy can be maintained, owing to the proposed method. The proposed method can greatly improve the positioning accuracy, as compared with traditional pseudorange+Doppler GPS/IMU tightly coupled navigation systems. [ABSTRACT FROM PUBLISHER]

With the increasing demand of spectrum and emergence of mobile devices, a cloud radio access network (C-RAN) is a promising technology to improve network capacity and coverage. The key concept of the C-RAN is to separate the radio function unit in remote radio heads (RRHs) from the digital function unit in baseband units (BBUs). This separation facilitates efficient spectrum and infrastructure sharing in the C-RAN. This paper considers the cooperative interference management among RRHs in the C-RAN. The RRHs can form coalitions to mitigate intra-interference and jointly serve their subscribers. To characterize RRH performance under the coalition, this paper develops two signal-to-interference-plus-noise-ratio (SINR)-based downlink throughput models of RRH, where one adopts tools from stochastic geometry to capture the interference from vehicular users (VUs) belonging to noncooperative RRHs, and another ignores the VU interference. In this paper, a coalition formation game is formulated to model the situation in which RRHs of C-RAN can make an individual decision to cooperatively serve their VUs if the throughput of the RRH can be improved. To obtain the solution of the proposed game, we develop a distributed coalition formation algorithm and analyze the stability of the coalition structure using a Markov chain model. Simulation results show that, as compared with the noncoalition and grand coalition, our distributed coalition formation can improve the C-RAN throughput by at least 20% and 80%, respectively. Furthermore, according to extensive simulation, we can define the conditions needed for RRHs to form a coalition and obtain higher throughput. [ABSTRACT FROM PUBLISHER]

This paper discusses a practical design of nonlinearity preprocessors to be used in a receiver for mitigating performance degradation in an impulsive noise environment. A simple method is proposed for a blanker and a soft limiter to calculate a blanking and a clipping threshold, respectively. In addition, to evaluate the bit error performance of a receiver with the proposed nonlinearity preprocessors, this paper introduces an approach using a periodic pulse train function and Fourier series. When a nonlinearity preprocessor is used, since the output samples show a truncated probability density function, it is generally difficult to evaluate the bit error performance of a receiver. Analytical and simulation results show that the thresholds computed by the proposed method are near optimal in terms of efficacy function and that the error performance of the proposed nonlinearity preprocessors matches well with that of the ideal design of nonlinearity preprocessors with optimal thresholds. [ABSTRACT FROM PUBLISHER]

Vehicular ad hoc networks (VANETs) experience large-scale high-speed mobility and volatile topology. VANETs may therefore experience intermittent connections and may occasionally be unable to guarantee end-to-end connections. This gives the medium access control (MAC) layer the opportunity to adapt its transmission strategy to the current unstable wireless connections to improve transmission efficiency. In this paper, we propose an adaptive frame length aggregation scheme (AFLAS) for VANETs, which is designed to improve transmission efficiency and increase data throughput. In our scheme, the incoming data packets from higher layers are queued separately in the MAC layer to wait for transmission opportunities. Suitable aggregation frame lengths are calculated according to the current wireless status and applied in the MAC layer at the onset of data transmissions. In this paper, we analyze and apply our AFLAS strategy to two current frame aggregation schemes in IEEE 802.11. We also report on the performance evaluation of our scheme. Our results exhibit significant improvement results in data throughput, retransmissions, overheads, and transmission efficiency in comparison with nonadaptive aggregation schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate antenna selection (AS) methods for bidirectional (BD) full-duplex multiple-input–multiple-output (MIMO) systems in which antennas at each node can be selected to either transmit or receive. In this configuration, we first analyze the average sum rate of the optimal AS scheme that finds the best antenna set solution by examining all the possible candidates. The result provides insight into which transmit and receive antenna configuration improves the average sum-rate performance of the AS scheme. Then, we present a new AS algorithm that achieves near-optimal sum-rate performance with much reduced complexity compared with the optimal AS scheme. From simulation results, we verify that our sum-rate analysis for the optimal AS scheme matches the numerical results and confirm that, by employing the proposed AS algorithm, a performance gain of 15% is achieved. [ABSTRACT FROM PUBLISHER]

This paper analyzes the ratio of transmit antennas to receive antennas at the base station (BS) in full-duplex multiuser multiple-input–multiple-output (MU-MIMO) systems with large-array BS and half-duplex multiantenna users. We consider a full-duplex BS with a block diagonalization (BD) precoder for downlink transmission and a BD receive filter for uplink reception. We derive the approximated downlink sum-rate considering the inter-user interference, and the uplink sum-rate considering the self-interference (SI), for large numbers of BS antennas. Based on the analysis, we formulate an optimization problem in terms of the ratio of transmit antennas to receive antennas to maximize the sum-rate. The analysis shows that the antenna ratio for maximizing the sum rate converges to the ratio of downlink streams to uplink streams as the number of total BS antennas goes to infinity. Simulation results confirm the analysis and show that the BS using the derived antenna ratio in the full-duplex MU-MIMO system can achieve about a 10∼20 b/s/Hz performance gain compared with the BS using an equal number of transmit and receive antennas. [ABSTRACT FROM PUBLISHER]

This paper studies the electronically steerable parasitic array radiator (ESPAR) antenna as a solution for beam pattern switching to implement blind interference alignment (BIA). The ESPAR antenna uses a single radio-frequency (RF) chain, and its beamforming is achieved by simply tuning the reactance loads of parasitic elements. Furthermore, ESPAR's beam pattern can be designed to enhance the received signal-to-noise ratio (SNR), thereby improving the performance of BIA. The focus of this work is the design of the ESPAR beam pattern to realize and improve BIA. In the first approach, each receiver ESPAR antenna dynamically selects the proper beam patterns from among the sector beam patterns, which are pre-designed to access different angular sectors with constant optimal antenna efficiency. We also propose a singular value decomposition (SVD) beamforming method, by means of the available channel state information at the receiver and a dynamic matching network for a high antenna efficiency. The simulation results illustrate the improvement of BIA with proposed methods, especially in the low and moderate SNR region, due to ESPAR's beamforming capability. [ABSTRACT FROM PUBLISHER]

This paper investigates low-complexity joint interference avoidance and desired link improvement for single-channel allocation in multiuser multiantenna access points (APs) for open-access small cells. It is considered that an active user is equipped with an antenna array that can be used to suppress interference sources but not to provide spatial diversity. On the other hand, the operation of APs can be coordinated to meet design requirements, where each of which can unconditionally utilize assigned physical channels. Moreover, each AP is equipped with uncorrelated antennas that can be reused simultaneously to serve many active users. The analysis provides new approaches to exploit physical channels, transmit antennas, and APs to mitigate interference, while providing the best possible link gain to an active user through the most suitable interference-free channel. The event of concurrent service requests placed by active users on a specific interference-free channel is discussed for either interference avoidance through identifying unshared channels or desired link improvement via multiuser scheduling. The applicability of the approaches to balance downlink loads is explained, and practical scenarios due to imperfect identification of interference-free channels and/or the scheduled user are thoroughly investigated. The developed results are applicable for any statistical and geometric models of the allocated channel to an active user, as well as channel conditions of interference users. They can be used to study various performance measures. Numerical and simulation results are presented to explain some outcomes of this paper. [ABSTRACT FROM PUBLISHER]

This paper investigates collaborative spectrum sharing (CSS) for which a cognitive secondary transmitter acts as a decode-and-forward (DF) relay for two primary users (PUs) occupying an interfering multiple-access channel. PUs are assumed to send their signals simultaneously; hence, interference between the primary signals exists due to the multiple-access nature. The secondary user (SU) selects and forwards one of the PU's signals to a desired destination, and at the same time, the SU also transmits its own signal only if it is not harmful to PUs. The selection of a primary signal to relay is investigated, depending on SU's knowledge of two primary source–destination channels, for which closed-form outage probabilities for PUs and SU are provided accordingly. With the help of the closed-form PU's outage probability, an optimal selection strategy between the primary signals and an optimal power allocation between the primary and secondary signals are also obtained in closed form, which minimizes SU's outage probability while keeping the PU's outage performance at an SU-free level. Numerical investigation is used to verify and illustrate the analysis given in this paper. Numerical results also show that the SU's performance can vary significantly according to the amount of channel knowledge that the SU can have. [ABSTRACT FROM PUBLISHER]

Integrated satellite terrestrial networks and non-orthogonal multiple access (NOMA) have been confirmed to be promising and effective approaches to achieve substantial performance gains for future wireless paradigms. This paper studies the effect of hardware impairments (HIs) on the secrecy performance of NOMA-based integrated satellite multiple-terrestrial relay networks (ISMTRNs). Particularly, we consider two important wiretapping cases: Case I, colluding case: all eavesdroppers cooperatively overhear the information; and Case II, non-colluding case: one eavesdropper with the best wiretapping quality is chosen to overhear the main channel information. Specially, the closed-form expressions for the secrecy outage probability (SOP) of the considered NOMA-based ISMTRNs in the presence of the above two eavesdropping cases and partial relay selection scheme are obtained. To obtain further insights in high signal-to-noise ratios (SNRs) regime, the asymptotic analysis of SOP with two considered cases are also derived, which give efficient means to evaluate the benefit of NOMA scheme and the impacts of HIs on the SOP. Moreover, we obtain Monte Carlo (MC) simulations for the secrecy energy efficiency (SEE). [ABSTRACT FROM AUTHOR]

While 5G is being deployed all around the world, the industry and academia start the investigation of 6G. Network function virtualization (NFV) is seen as the key enabler towards the flexible resource management and sharing of 6G networks. The main idea of NFV is to decouple the physical devices from the specific functions that run on them. In NFV, virtual network service (NS) is modeled as a service function chain (SFC). The challenges in SFC description, composition, embedding, and scheduling are key issues in NFV. In this paper, we focus on the joint SFC embedding and scheduling for NFV in 6G networks. With the assistance of sensing the physical node resource abilities, we propose a novel SFC embedding and scheduling algorithm, which is named as RA-SFC-6G. A new service is first composed as an SFC which is an ordered sequence of virtual network functions (VNFs). Afterwards, our RA-SFC-6G algorithm will select the physical nodes with stronger resource abilities and abundant resources to accommodate the SFC. In addition, the NS is guaranteed to be implemented without violating the NS maximum allowed scheduling time. If violated, our RA-SFC-6G can re-embed and re-schedule the violated VNFs to suitable positions. In order to validate our RA-SFC-6G performance, we do the experiment work. Experiment results show that our RA-SFC-6G achieves at least 10% higher SFC acceptance ratio than the previous counterparts and the typical heuristics. [ABSTRACT FROM AUTHOR]

This paper deals with a key problem in WiFi fingerprint-based localization, namely how to sample a sufficient number of received signal strength (RSS) measurements during an offline site survey. To this end, a probabilistic framework is firstly presented to characterize the ability of distinguishing two fingerprints, and is then applied in both the ideally infinite sampling case and the realistically finite sampling case with correlated samples. On these grounds, it is shown that the Euclidean distance between the vectors of mean RSS measurements at any two positions is the key factor of determining localization performance, and how several other factors affect localization performance. More importantly, based on the central limit theory, a quantitative analysis is conducted to describe the degradation in localization performance introduced by finite and correlated samples. In addition, provided that correlated samples satisfy the first order autoregressive model, an explicit formula is derived to describe the relationship between the correlation coefficient and the sampling sizes, which can be employed to guide the offline site survey. Extensive simulations are conducted to confirm the effectiveness of the probabilistic framework as well as the correctness of different analytical results, and an experiment is also carried out for validation. This paper not only helps to understand the basic mechanism of WiFi fingerprint-based localization, but also provides insightful guidelines for efficiently building a fingerprint database. [ABSTRACT FROM AUTHOR]

This paper presents a new linear eddy current speed sensor with rectangular-shaped coils. The excitation coil and the pick-up coil have a perpendicular configuration without a magnetic yoke. The proposed sensor is shorter than the previous designs. The sensor works for a conductive moving target; in this paper we present calculations and an experimental verification for solid iron and aluminum moving part materials. A novel 3D analytical method is presented for the description and for the design of an eddy current speed sensor that is fast and has high precision. The source fields and the reaction fields caused by induced eddy currents are separated in our 3D analytical method, which facilitates an enhanced investigation of the features of the speed sensor. Evaluations of the effects of the moving part material and of coil lift off on the performance of the speed sensor are made with the use of a 3D analytical method. Measurements are performed for an eddy current speed sensor at different speeds up to 11.65 m/s and at different frequencies with a novel analytical model in terms of the induced voltage in the pickup coil versus speed. Simplicity and high precision are the main advantages of the proposed speed sensor. The achieved linearity error is 0.47% (measured) up to 11.6 m/s, and 0.43% (calculated) up to 117 m/s (420 km/h). [ABSTRACT FROM AUTHOR]

The dynamic interaction of vehicles/bridges is an important part of the research field of the Electromagnet Suspension (EMS) maglev train. However, multiple factors affect the dynamics of the coupling system, which increases the complexity of the vehicle-bridge coupling system, and makes it difficult to analyze. Herein, combining the advantages of theoretical derivation and numerical calculation, a fast and accurate analysis method of maglev vehicle and bridge system is proposed to analyze the influence of bridge and controller on the dynamics of the maglev system. This work is directed to the Changsha maglev express line, in which the mathematical equations for the vehicle- bridge system is presented. Then the influence of the parameter on the system is analyzed. Finally, the vibration experimental test system is set up, and the vibration test of the maglev vehicle bridge is tested by the test scheme, and the experimental results data are given. The test results of vibration acceleration are in good agreement with the calculation results of the proposed method, which verifies the accuracy of the model and the analysis method. Therefore, the research in this paper can provide theoretical guidance for Maglev engineering, and the analysis method in this paper can also be used in the study of other vehicles, such as the high-speed maglev train. [ABSTRACT FROM AUTHOR]

Due to the problems of high bit error rate and delay, low bandwidth and limited energy of sensor nodes in underwater acoustic sensor network (UASN), it is particularly important to design a routing protocol with high reliability, strong robustness, low end-to-end delay and high energy efficiency which can flexibly be employed in dynamic network environment. Therefore, a reinforcement learning-based opportunistic routing protocol (RLOR) is proposed in this paper by combining the advantages of opportunistic routing and reinforcement learning algorithm. The RLOR is a kind of distributed routing approach, which comprehensively considers nodes’ peripheral status to select the appropriate relay nodes. Additionally, a recovery mechanism is employed in RLOR to enable the packets to bypass the void area efficiently and continue to forward, which improves the delivery rate of data in some sparse networks. The simulation results show that, compared with other representative underwater routing protocols, the proposed RLOR performs well in end-to-end delay, reliability, energy efficiency and other aspects in underwater dynamic network environments. [ABSTRACT FROM AUTHOR]

Intelligent mobile vehicles asks for the ability to learn to comprehend immediate surroundings similar to human cognition and autonomously navigate in an unknown scene. Although simultaneous localization and mapping (SLAM) can construct a geometrically surrounding map, the map contains little semantic information. This paper presents a novel stereo visual-inertial system with loop closure detection based on a semantic-topological map framework. In our system, a hybrid 3D point cloud semantic-topological mapping framework is used to realize autonomous navigation simply by providing a map for path planning and meanwhile for storing semantic information under a dynamic environment. A stereo visual-inertial system can obtain more accurate visual-inertial odometry than a monocular system, and a visual-inertial system is capable of real-time map correction when the localization module detects a loop closure. This paper adopts state-of-the-art Mask R-CNN components to obtain 2D semantic information and project it to a semi-dense 3D semantic-topological map built by stereo visual-inertial SLAM. We perform experimental evaluation of our proposed system on the EuRoC MAV datasets and we also compare it with other competitive methods. Our results demonstrate that the proposed method is more effective than the other competitive methods. [ABSTRACT FROM AUTHOR]

The technical challenges, e.g. the mobility management and the offloading process, hinder the conventional cellular systems to meet the huge data traffic requirements of the next generation mobile communications. The traditional system (e.g dual-connectivity (DC)) has been proposed to improve the mobility management, however, it will inherit the big trade-off in the offloading process between the energy consumption for the small cell (SC) discovery (SCD) process and the efficiency of utilizing the system resources (e.g. frequency and signaling). In this paper, we present a framework to model the potential offloading opportunities as well as the offloading loss when a typical user equipment (UE) performs the inter-frequency (IRF) scan periodically. The proposed framework also studies the impact of the SCD on the energy efficiency. To improve the system performance and reduce the power consumption at the UEs, a new scheme, trio-connectivity (TC), is proposed in this paper to tackle the aforementioned challenges. The TC includes three planes: control-plane (C-plane), user-plane (U-plane) and indication-plane (I-plane). The I-plane works as an indicator to help the UE to identify and discover the SCs in the system prior to offloading. The role of the I-plane is to keep the SCD on one frequency channel regardless of the number of frequency channels in the system. In the proposed offloading mechanism, some of the energy consumption is transferred from the UE to the network. By using the proposed framework, UE energy efficiency and system energy efficiency as well as the total energy consumption are derived as performance metrics to compare between the TC and the DC. The results show that the TC can outperform the DC in dense cellular systems. [ABSTRACT FROM AUTHOR]

3D LiDAR maps are playing a more and more important role in intelligent vehicle localization. In this paper, the proposed SeqPolar localization method consists of two parts. The first part is a novel node-based LiDAR map representation method, termed polarized LiDAR map (PLM), and the second is a map matching algorithm based on a second-order hidden Markov model (HMM2) for vehicle localization. Unlike existing 3D LiDAR map, which is usually constructed by accumulating 3D LiDAR clouds collected at different times, the proposed polarized LiDAR map is generated from a set of nodes. Each node consists of three elements: a polarized LiDAR image, scene features extracted from the polarized LiDAR image, and sensor pose. The polarized LiDAR image encodes 3D coordinates and reflectivities of the 3D LiDAR cloud using a multi-channel image format, a more concise, straightforward, and structured representation of the 3D LiDAR cloud. In the localization step, we propose an HMM2-based method to match a sequence of input polarized images within the map nodes and find the nearest node from the PLM. Afterward, the vehicle is readily localized from the matched map node with 3D registration. The proposed SeqPolar localization method has been validated with the actual field dataset and the public KITTI database. Experimental results demonstrate that the proposed HMM2-based matching method can achieve up to 98% accuracy to find the nearest node from PLM. Moreover, the SeqPolar localization method based on the pre-built PLM can achieve 30-centimeter localization accuracy in average on both test datasets. [ABSTRACT FROM AUTHOR]

As for fuel cell hybrid electric vehicle equipped with battery (BAT) and ultracapacitor (UC), its dynamic topology structure is complex and different characteristics of three power sources induce challenges in energy management for fuel economy, power sources lifespan, and dynamic performance of the vehicle. In this paper, an energy management strategy (EMS) based on a hierarchical power splitting structure and deep reinforcement learning (DRL) is proposed. In the higher layer strategy of the proposed EMS, the UC is employed to supply peak power and recover braking energy through the adaptive filter based on fuzzy control. Then, the integrated DRL and equivalent consumption minimization strategy framework is proposed to optimize the power allocation of fuel cell (FC) and BAT in the lower layer, to ensure the highly efficient operation of FC and reduce hydrogen consumption. And the action trimming based on heuristic technique is proposed to further restrain the adverse effect of sudden peak power on FC lifespan. The simulation results show the proposed EMS can make the output of FC smoother, improve its working efficiency to alleviate the stress of BAT, and increase by 14.8% compared with the Q-learning strategy in fuel economy under WLTP driving cycle. Meanwhile, the obtained results under UDDSHDV show fuel economy of the proposed EMS can reach dynamic programming (DP) benchmark level of 89.7 $\%$. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a mobile edge computing (MEC) network, where the user has some computational tasks to be assisted by multiple computational access points (CAPs) through offloading. We consider practical communication scenarios with limited spectrum resources, and the cochannel interference arising from the aggressive reuse of frequency severely degrades the system offloading performance. To enhance the system performance, we provide three CAP selection criteria to choose one best CAP among multiple ones. Specifically, criterion I maximizes the computational capability at the CAP, criterion II minimizes the interfering power, while criterion III maximizes the instantaneous channel gain of data link. In time-varying channel environments, the CAP selection may be outdated, which deteriorates the system performance. For the three criteria, we evaluate the system outage probability in the outdated channel state information (CSI) by taking into account the latency, energy consumption and data rate, and provide the analytical and asymptotic expressions of outage probability, from which we obtain some critical insights on the system design. Simulation results are finally demonstrated to verify the proposed studies. In particular, criterion III under the perfect CSI can achieve the system whole diversity order coming from multiple CAPs. [ABSTRACT FROM AUTHOR]

Security issue in underwater visible light communication (UVLC) arises mainly due to the scattering effect wherein numerous photons are statistically generated when a light beam strikes a water molecule. This paper considers an underwater communication scenario wherein a floating vehicle (FV) transmitter that is equipped with multiple light-emitting diodes (LEDs) communicates with the two legitimate near-end and far-end underwater vehicles (UVs) in presence of an eavesdropper. In particular, two non-orthogonal multiple access (NOMA) technology-based optimal LED selection (OLS) and suboptimal LED selection (SLS) schemes are proposed to select a LED that can transmit the information with the highest secrecy rate against active/passive eavesdropping attacks. Furthermore, the FVT transmits the information to both UVs with the selected LED only. Utilizing the successive interference cancellation (SIC) characteristic, this paper derives the closed-form secrecy outage probability expressions for both single-LED and multi-LED transmission strategies for both known and unknown CSI. The security performance of the proposed multi-LED NOMA-UVLC is compared with the conventional single-LED NOMA-UVLC under the effects of air bubbles for both fresh and salty water types. In addition, the validity of the numerical results is verified through Monte-carlo simulation analysis. [ABSTRACT FROM AUTHOR]

With the deep integration between the unmanned aerial vehicle (UAV) and wireless communication, UAV-based air-to-ground (AG) propagation channels need more detailed descriptions and accurate models. In this paper, we aim to conduct cluster-based characterization and modeling for AG channels. To our best knowledge, this is the first study that concentrates on the clustering and tracking of multipath components (MPCs) for time-varying AG channels. Based on measurement data at 6.5 GHz with a bandwidth of 500 MHz, we first estimate potential MPCs utilizing the space-alternating generalized expectation-maximization (SAGE) algorithm. Then, we cluster the extracted MPCs by employing K-Power-Means (KPM) algorithm under multipath component distance (MCD) measure. For characterizing time-variant clusters, we exploit a clustering-based tracking (CBT) method, which efficiently quantifies the survival lengths of clusters. Ultimately, we establish a cluster-based channel model, and validations illustrate the accuracy of the proposed model. This work not only promotes a better understanding of AG propagation channels but also provides a general cluster-based AG channel model with certain extensibility. [ABSTRACT FROM AUTHOR]

This paper explores the feasibility and scope of co-channel coexistence between a low data rate Orthogonal Frequency Division Multiplexing (OFDM) secondary network and a digital television (DTV) broadcast network operating in the same area. Since DTV receivers do not transmit, neither the presence nor the impact of interference from the secondary network on these DTV receivers can be known. Consequently, conventional spectrum sensing techniques cannot be employed effectively. This paper proposes to compensate the lack of feedback by combining the available information about population distribution in the region - ranging from coarse population density estimates to accurate geospatial maps - with better estimation of interference using a data-driven technique called Ordinary Kriging. Radio Environment Maps constructed using the Kriging method from field-reported observations from the secondary nodes are used to obtain better accuracy than the conventional statistical models. The estimates are then used to compute communication parameters for each secondary link in terms of power, number of active subcarriers, and active time slots, while keeping the average interference in the DTV network within threshold bounds. Thus, the viability of such co-channel license-exempt operation of secondary networks in the DTV black and grey spaces for low data rate applications in densely populated urban areas and higher data rate capabilities for sparsely populated rural areas is established. [ABSTRACT FROM AUTHOR]

Solid-state transformers (SST) are emerging technologies to replace the conventional low-frequency main transformer (MTR) in railway vehicles. In order to isolate the load side from the AC 25 kV high-voltage (HV) side and to reduce the whole size of the SST, HV insulation and high-frequency transformers should be used in DC/DC converters. Furthermore, due to the severe constraint of installation space and difficulty of heat dissipation management in the bottom of railway vehicles, high-power density and minimum transformer loss should be considered. To satisfy such design requirements of the proposed SST for railway vehicles, high efficiency integrated transformers, which inherently have leakage inductance, are proposed for dual-active-bridge (DAB) converters in this paper. In order to obtain appropriate equivalent leakage inductance for the DAB converters, a calculation methodology for the leakage inductance has been introduced and verified by simulation. Two separated winding structures in the center-core are adopted to improve the core loss, and appropriate winding turns with 60 kV HV insulation capability are selected, according to the proposed design procedure of the integrated transformers. In order to compare the proposed transformers with the conventional transformer having additional inductors and to verify the major characteristics of the transformers, two 125 kW proposed transformers and conventional transformers have been built and evaluated by an 250 kW SST module, operating at 10 kHz switching frequency. Under a 125 kW full-load condition, 99.7% transformer efficiency was obtained by the proposed integrated transformers, which are 4.7% smaller and 7.0% lighter than the conventional transformer. As a result, 26°C maximum temperature improvement has been obtained and 60k V HV insulation capability has been satisfied by the proposed integrated transformers. [ABSTRACT FROM AUTHOR]

Channel predictions are important to achieve high spectral efficiency for high-mobility vehicles. Channel extrapolation, used by many prediction methods, suffers from a limited prediction horizon in difficult radio environments. The predictor antenna (PA) concept provides the prediction horizons required for efficient transmission to fast-moving vehicles by measuring the channel ahead of time with an extra antenna placed on the vehicle. This paper presents a general framework that addresses the practical signal processing challenges of the PA concept. It is adaptable to a vast variety of vehicular deployment, mobility, and communication scenarios. A new theoretical prediction normalized mean-squared error (NMSE) expression is derived based on the presented framework. The framework is demonstrated by applying it to extensive channel measurements and comparing the PA predictions to Kalman-based channel predictions and outdated channel estimates. By studying the impact of vehicular velocity and radio environment on the prediction performance, it is shown that PA prediction is weaker at low velocities, where Kalman prediction methods are sufficient, but is uncontested at high velocities in environments without a dominating path. At high velocities in dominating path environments, the Kalman predictor provides usable predictions, but it is still outperformed by the PA predictions. [ABSTRACT FROM AUTHOR]

Computation offloading is an effective method in mobile edge computing (MEC) to relieve user equipment (UE) from the limited computation resource and battery capacity. Meanwhile, simultaneous wireless information and power transmission (SWIPT) can be applied to MEC to extend the operating time of the equipment. However, in multi-user network environment, diverse computation task requirements and changeable network channel states make it challenging to obtain offloading strategy timely and accurately. To address the issue, we propose an intelligent computation offloading scheme (iCOS) based on enhanced priority deep deterministic policy gradient (EPDDPG) algorithm to minimize the energy consumption of all the UEs by jointly optimizing the offloading decision, the central processing unit (CPU) frequency and the power split ratio in a dynamic SWIPT-MEC network. In particular, we improve the traditional fully-connected network structure to obtain both discrete and continuous action outputs, and accelerate neural network parameter updates by using prioritized experience tuples. Furthermore, we use dynamic voltage and frequency scaling (DVFS) technology to dynamically adjust the CPU frequency of local computing, and employ SWIPT technology to balance the charging and communication according to the obtained strategy. Simulation results show that the algorithm proposed in this paper can effectively reduce the energy cost of UEs, and complete more computation tasks within the delay limit. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the linear precoder design for three dimensional (3D) massive multi-input multi-output (MIMO) downlink with uniform planar array (UPA) and imperfect channel state information (CSI). We introduce a beam based statistical channel model (BSCM) by using sampled steering vectors, and then an a posteriori channel model which includes the channel aging is established. On the basis of the a posteriori channel model, we consider the robust precoder design by maximizing an upper bound of the expected weighted sum-rate under a total power constraint. We derive two concave minorizing functions of the objective function. With these minorizing functions and the minorize-maximization (MM) methodology, we derive two iterative algorithms that converge to stationary points of the optimization problem. Simulation results show that the proposed precoders can achieve a significant performance gain than the widely used regularized zero forcing (RZF) precoder and the signal to leakage noise ratio (SLNR) precoder in median to high mobility scenarios. [ABSTRACT FROM AUTHOR]

The work presented in this paper describes a multi-issue negotiation protocol between active consumers and a management platform in order to establish load coordination in a highly congested network. The multi-issue negotiation protocol considers simultaneously the consumption interval, the price, and the size of the energy packages, which is the main contribution of this work. Regarding the implementation methodology, the proposed algorithms have been implemented using MATLAB classes that allow emulating the behaviour of a multi-agent system in which each vehicle is an agent that interacts with the platform, which is another agent. In the present work, and without loss of generality, the algorithm is applied to coordinate the charging of electric vehicles (EVs) in a distribution network in which building loads represent critical loads. The algorithm is tested in a realistic environment, and its stability and performance are evaluated. Furthermore, the description of the algorithm is provided in a generic form, and it could be applied to any other scenario. [ABSTRACT FROM AUTHOR]

The joint transmission scheme of polar codes and sparse code multiple access (SCMA) has been regarded as a promising technology for future wireless communication systems. However, most of the existing polar-coded SCMA (PC-SCMA) systems suffer from high latency caused by the feedback iteration and list decoding. In addition, the error performance of PC-SCMA systems is unsatisfactory for ultra-reliable transmission. Inspired by the compelling benefits of non-binary polar codes, in this paper, we design a non-binary polar-coded SCMA (NB-PC-SCMA) system with a free order matching strategy to address the issues of delay and reliability. Specifically, we first formulate a joint factor graph for NB-PC-SCMA and propose a non-binary successive cancellation list (NB-SCL) and damping based joint iterative detection and decoding (NSD-JIDD) multiuser receiver to improve the BER and latency performance. Then, a lazy-search based NB-SCL (L-NB-SCL) decoding is proposed to reduce the computational complexity by simplifying the path search pattern of the list decoder. After that, we modify the update of user nodes for SCMA detection to improve the convergence error and finally propose the improved NSD-JIDD (ISD-JIDD) algorithm, which can avoid redundant operations by exploiting L-NB-SCL decoding. Simulation results show that the proposed NB-PC-SCMA system achieves better bit error rate (BER) performance and considerable latency gain when compared to its counterparts. In particular, the proposed ISD-JIDD can achieve similar BER performance of NSD-JIDD with less complexity. [ABSTRACT FROM AUTHOR]

In order to improve the trajectory tracking accuracy and vehicle lateral stability, the paper proposes a lateral and longitudinal dynamics control framework of autonomous vehicles considering multi-parameter joint estimation. First, the multi-parameter joint estimation based on adaptive unscented Kalman filter (AUKF) is constructed to decouple and estimate the longitudinal position of vehicle's center of gravity (CG), tire-road friction coefficient (TRFC), tire cornering stiffness (TCS), tire vertical force (TVF) and road grade. Then, focusing on the large lateral acceleration condition, a lateral control based on the optimal front-tire lateral force is proposed by constructing the linear quadratic regulator (LQR) and combining the multi-parameter joint estimation. Additionally, a longitudinal control based on the drive and brake force compensation to realize the accurate speed tracking by combining road slop estimation is achieved. The fuzzy system employs the drive and brake force deviation as the input to implement the compensation of the throttle and brake. The proposed estimation and control framework are verified by co-simulation on PreScan and CarSim preliminarily. In order to further verify the effectiveness and practicability of algorithm, experiments are implemented on an autonomous vehicle platform, a hybrid Lincoln MKZ. Simulation and experimental results show that the proposed estimation and control framework possess excellent performance and enhance the tracking accuracy and lateral stability. [ABSTRACT FROM AUTHOR]

Longitudinal velocity, lateral velocity, and front wheel steering angle are crucial states for vehicle active safety features. However, direct measurement of these variables requires expensive measurement instruments and can be easily affected by vehicle nonlinear dynamics, outliers and noise pollution. Moreover, unknown inputs bring great challenges to their accurate estimation. Therefore, this paper develops a novel robust unscented M-estimation-based filter (RUMF) for vehicle state estimation with unknown driver steering torque. The nonlinear system model is constructed based on the vehicle dynamics model. Unscented transformation (UT) and statistical linearization are implemented to transform the nonlinear process and measurement function into a linear-like regression form with data redundancy to achieve outlier suppression. Then, an M-estimation-based iterated algorithm is designed to address process uncertainty and innovation and observation outliers for robust vehicle state estimation. The iteratively reweighted least-squares (IRLS) method based on the M-estimation methodology is utilized for unknown input estimation. Simulations and experimental results compared with extended Kalman filter (EKF) and particle filter (PF) have verified the effectiveness and robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]