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Integrating optical and wireless broadband access networks is an important step in achieving fixed mobile convergence in metropolitan areas. In this paper, a promising network architecture by integrating a passive optical network and a wireless cooperative network is investigated, in which intercell cooperative transmission is incorporated. Our goal is to exploit both economic and performance benefits. To achieve a cost-effective deployment and meet long-term performance requirements, this paper addresses the issue of dimensioning and site planning (DSP). We provide a complete formulation to capture the challenges behind network deployment. A number of long-term design subjects are jointly considered in a unified optimization framework, including infrastructure placement, base station user allocation, and resource breakdown assignment. To reduce the computation complexity, the DSP problem is decomposed into two subproblems. An approach is further developed to reformulate the problem into a solvable mixed integer linear program. Moreover, we conduct case studies to validate the formulation, in which performance gains are demonstrated in terms of total infrastructure cost reduction, spectral efficiency improvement, and scalability in capacity enhancement.

The aim of this paper is to present the practical control structure (PCS) and energy management strategy of a testbed hybrid electric vehicle (HEV). This vehicle is equipped with batteries, a supercapacitor system, and a fuel cell system (FCS). The PCS, based on the energetic macroscopic representation methodology, is used to evaluate and compare the different energy management strategies to be implemented in the vehicle. This paper introduces a dynamic strategy to manage the energy in the hybrid electric vehicle; this strategy uses a fuzzy logic controller and considers the slow dynamics in the FCS, the vehicle speed, and the state of charge in the supercapacitors.

Indirect field-oriented control, direct field-oriented control, and direct torque control are the most widely used instantaneous torque control techniques for the drive system of alternative energy vehicles (AEVs). This paper evaluates three candidate alternating-current machines and investigates the suitability of different control techniques for the drive systems of battery-powered electric vehicles, hybrid electric vehicles, and integrated starter alternators. Accurate flux and torque estimation is the core of any opted control technique for all types of AEV drive systems. Therefore, an accurate closed-loop voltage model flux and torque estimator that is insensitive to stator resistance variation has been designed. This paper also analyzes loss model control and search control (SC) techniques for the drive system's efficiency optimization and proposes an offline SC efficiency optimization technique. Experimental results are presented to demonstrate the performance of the proposed flux and torque estimator and efficiency optimizer.

The main aim in the control of a hybrid electric vehicle (HEV) is to decrease the fuel consumption and emissions without significant loss of driving performance. The performance of the vehicle in terms of fuel economy and emissions is very much dependent on the vehicle's supervisory control strategy. In this paper, the equivalent consumption minimization strategy (ECMS) is developed with a novel approach for the charge sustaining of the batteries to provide an overall improved optimization performance for series hybrid electric vehicles (SHEVs), considering the efficiencies of the internal combustion engine (ICE), generator, and battery. Another novelty is the development of a combined map, which simultaneously facilitates the optimization of the fuel consumption and multiple emission components, unlike most past studies that have concentrated on one component at a time. After the derivation of the cost map, the algorithm is divided into two main parts. The first part optimizes the engine-generator set (GENSET), and the second part determines how much power is needed from the GENSET according to the ECMS. The algorithm is implemented using generic emission and fuel consumption maps of an actual mid-sized series hybrid bus to reduce the desired emissions. The hybrid electric vehicle in consideration is converted from a conventional bus that is driven by an ICE. The performance of the novel ECMS strategy is compared with the conventional vehicle, as well as the SHEV version that is driven by an on-off strategy. In addition to reduced fuel consumption, the results of this paper demonstrate a significant reduction of 14.58% in CO2 production with ECMS, whereas the on-off control strategy achieves only 6.47% reduction over the conventional vehicle.

This paper studies the charging strategies of an Li-ion battery with a focus on the battery's power loss model. It is found that when the temperature is assumed constant, constant current/constant voltage (CC/CV) is near optimal for energy loss minimization. However, when the temperature is considered as a state variable, an optimal profile different from CC/CV is found. This new profile can be used to warm-up batteries during cold days, hence reducing the need for existing battery heating systems. As a result of the elevated battery temperature, significant energy savings can be achieved if the vehicle is used soon after the charging process ends. In this paper, the form of the optimization problem resembles a classic form, with the peculiarity of being highly nonlinear and time varying. The charging strategies resulting from this study will have significant impact on how plug-in hybrid electric vehicles (PHEVs) are charged and utilized.

The advancement of electronic technology has made significant contributions to the safety and convenience of modern vehicles. New intelligent functionalities of vehicles have been implemented in a number of electronic control units (ECUs) that are connected to each in vehicle control networks (VCNs). However, with the rapid increase in the number of ECUs, VCNs currently face several challenges, e.g., design complexity, space constraints, system reliability, and interdependency. Considering these factors, the complexity of the VCN design problem exponentially increases, which means that the problem cannot be solved within a reasonable time using conventional optimization techniques. In this paper, we report a new methodology for the optimal design of VCNs. An analytical model was derived to examine the fundamental characteristics of the VCN design problem. Compared with the case of a conventional data network, which typically considers temporal scheduling over a fixed physical topology, the VCN design problem should also consider spatial constraints, e.g., volume, position, and weight. Moreover, the spatial constraints change during the solving procedure. Such temporal and spatial joint optimization problems with varying constraints incur extremely high computational complexity. To tackle the high complexity, this paper proposes a fast solution based on a repeated-matching method, which reduces the problem complexity from O(NNN) to O(NN3). By applying our methodology to a number of different real-world VCN design scenarios, this proposal can produce a 1% near-optimal design within a significantly reduced time.

This paper presents a methodology of calculating the optimal torque and speed commands for the engine-generator system of a series hybrid electric vehicle (HEV). In series HEVs, the engine-generator subsystem provides electrical energy to the dc link. This paper proposes an optimal control strategy of the engine-generator subsystem to generate a desired amount of energy within a given period of time. The optimization algorithm, based on trajectory optimization, determines the torque and speed reference signals for the engine-generator subsystem that achieve maximum efficiency. A simplified version of the controller is also presented for online implementation. The proposed control strategy is compared with nonoptimized control techniques, and simulation results show the improvements in energy efficiency.

Airbag systems have become an essential safety device for guaranteeing the physical well-being of drivers and their passengers. Unlike other safety devices, airbags are used as the last resort in a collision, and because they are directly linked to the life of the driver and passengers, the proper functioning of the system is an issue of paramount importance. Hence, to ensure the precision and reliability of airbag operation, it is necessary to design a robust crash algorithm. Currently, several companies are working to achieve an optimal deployment time for airbags in collisions by diversifying the type and location of crash-related sensors. Nevertheless, several problems must still be confronted. For instance, when a vehicle operates off road or when the sensor inside the airbag control unit (ACU) receives a powerful shock, the vehicle's airbags may inadvertently deploy, although no collision has occurred, because a crashlike signal is delivered to the ACU. Alternately, in a collision situation that requires airbag deployment, the crash algorithm may make an erroneous judgment with regard to the collision configuration and miss the time frame for airbag deployment or fail to deploy the airbags altogether. Such problems can be attributed to the following two major causes: 1) Only signals produced through crash tests are used in the design of crash algorithms, and 2) the algorithms themselves only utilize postcrash input from the relevant sensors. To resolve these issues, this paper proposes a precrash algorithm that generates information about the crash scenarios before a collision has occurred. The purpose of the precrash algorithm is to make judgments about the impending collision configuration prior to impact by estimating the behavior of frontal objects and to communicate this information to the crash algorithm to enable correct recognition of the crash scenarios. This paper also proposes a crash algorithm based on crash-related sensors for the verification of and interfacing with the proposed precrash algorithm. The limitations of existing crash algorithms, which deploy airbags using only postcrash signals, were resolved through the development of an integrative crash algorithm that combines the precrash and crash algorithms to reflect precrash information. The developed algorithm was verified by running a wide range of simulations using CarSim, based on data from real crash tests. The results showed that, compared with independently using the crash algorithm, adding precrash information estimation significantly improved the reliability of airbag deployment.

This paper presents a novel real-time tire-road friction coefficient estimation method that is independent of vehicle longitudinal motion for ground vehicles with separable control of the front and rear wheels. The tire-road friction coefficient information is of critical importance for vehicle dynamic control systems and intelligent autonomous vehicle applications. In this paper, the vehicle longitudinal-motion-independent tire-road friction coefficient estimation method consists of three main components: 1) an observer to estimate the internal state of a dynamic LuGre tire model; 2) an adaptive control law with a parameter projection mechanism to track the desired vehicle longitudinal motion in the presence of tire-road friction coefficient uncertainties and actively injected braking excitation signals; and 3) a recursive least square estimator that is independent of the control law, to estimate the tire-road friction coefficient in real time. Simulation results based on a high-fidelity CarSim full-vehicle model show that the system can reliably estimate the tire-road friction coefficient independent of vehicle longitudinal motion.

Real-time energy management of hybrid electric vehicles (HEVs) is a key point for performing effective fuel economy optimization. Offline methods have been developed for energy management optimization when the drive cycle is known. Online real-time methods can provide good results but can only ensure suboptimal management. In this paper, it is assumed that information about the route is available in advance. Using this knowledge, global optimization methods can be used in real-time control to approach optimal fuel consumption while keeping the state of charge (Soc) of the batteries at a desired level. Such a method is presented in this paper. The developed strategy is implemented in a real-time experiment using the power-hardware-in-the-loop (PHIL) principle. The measured fuel consumption and the obtained battery Soc trajectory demonstrate good performance of the proposed control. Author Keywords: Energy management , fuel consumption , hybrid electric vehicle (HEV) , optimization , power hardware in the loop (PHIL) .

This paper investigates a transmission scheme that is suitable for short-range multiple-input-multiple-output (MIMO) transmission. Since the distance between two array antennas that face each other is comparable with the size of the array antenna aperture in short-range MIMO, the propagation characteristics are greatly different from those in conventional MIMO. Unlike conventional MIMO, the optimal element spacing, which maximizes channel capacity, exists in short-range MIMO. Moreover, the channel capacity with optimal antenna spacing exceeds the ergodic capacity of independent identically distributed (i.i.d.) channels since optimal eigenvalue distribution, which can maximize channel capacity, is obtained in the short-range MIMO. In this paper, we focus on the actual transmission methods, because complex transmission schemes such as eigenmode transmission or maximum-likelihood detection are required to obtain ideal channel capacity. We clarify that the channel capacity obtained by zero forcing (ZF) at the receiver without beamforming at the transmitter is almost the same as that using eigenmode transmission when considering the optimal element spacing. The effectiveness of short-range MIMO communication is also clarified using a 4 × 4 MIMO testbed with actual signals based on the IEEE 802.11n standard. Simulated and measured results show that optimal element spacing is a key parameter in the short-range MIMO communication. We found that designing antenna arrays with optimal element spacing is a very effective approach to achieving a simple hardware configuration.

This paper presents a feasibility study into the application of a 100-V, 50-kHz high-frequency ac (HFAC) network for powering automotive electrical auxiliaries. The study is focused on motor-actuated loads and is divided into two sections. First, the investigation indicates the benefits of replacing low-torque dc motors with lighter and more efficient 400-Hz ac machines for applications such as electric fans, fuel pumps, or blower motors. A comparative examination of commercially available machines indicates space and weight reduction of more than 60%, and efficiency savings between 25% and 100% are possible. Second, the inquiry evaluates the viability of replacing existing dc/ac inverters with HFAC/ ac converters for high-torque ac machines as employed, for example, in electric- power-assisted steering (EPAS) or heating, ventilation, and air conditioning systems. Based on experimental and simulation results for a column-assist EPAS application employing a three-phase permanent-magnet synchronous motor, this paper shows that an HFAC drive is expected to reduce the voltage harmonic content below 50 kHz by at least 10% compared with the dc/ac inverter. However, the disadvantages of the former drive make it less attractive than the existing dc/ac circuit. Specifically, the EPAS motor torque ripple is expected to be approximately 2% higher compared with the dc counterpart drive. Further drawbacks of the HFAC/ac drive include high metal-oxide-semiconductor field- effect transistor (MOSFET) conduction losses, higher voltage harmonics above 50 kHz, and complex control requirements of the inverter. Conclusively, significant HFAC advantages for motor loads can only be attributed to machines with a nominal torque capability that is limited to 2 N ·m. However, given the number of such devices within a typical vehicle, this translates into a possible vehicle mass saving of 30 kg and a potential reduction in fuel consumption by 0.8 L/100 km

Improved fuel consumption and lower emissions are two of the key objectives for future transportation. Hybrid electric vehicles (HEVs), in which two or more power systems are combined, can meet these objectives through the capture and reuse of regenerated braking energy and through optimized use of the prime mover. However, more complicated power-management strategies are required for such vehicles. This paper explores the potential of applying to advanced power-management strategies for a diesel multiple-unit (DMU) train. These types of vehicles have multiple diesel engines that are commonly operated in a homogenous manner. This paper analyzes the potential energy savings that may be obtained through the independent operation of the engines. Two widely investigated power-management strategies that have been developed for HEVs have been applied to a typical DMU railroad vehicle. Dynamic programming (DP) strategies have been applied to the results produced by a single-train motion simulator to identify the optimal instant power distribution between the engines. An adaptive rule-based online strategy based on the optimization results from the DP solution is then proposed and realized using a nonlinear programming optimization algorithm. Both strategies indicate acceptable agreement and show a fuel cost reduction of around 7%, in comparison with the evenly split engine operation.

In this paper, the problem of joint multichannel cooperative sensing and resource allocation is investigated. A cognitive radio network with multiple potential channels and multiple secondary users is considered. Each secondary user carries out wideband spectrum sensing to get a test statistic for each channel and transmits the test statistic to a coordinator. After collecting all the test statistics from secondary users, the coordinator makes the estimation as to whether primary users are idle or not in the channels. When a channel is estimated to be free, secondary users can get access to the channel with assigned bandwidth and power. An optimization problem is formulated, which maximizes the weighted sum of secondary users' throughputs while guaranteeing a certain level of protection for the activities of primary users. Although the problem is nonconvex, it is shown that the problem can be solved by bilevel optimization and monotonic programming. This paper is also extended to cases with consideration of proportional and max-min fairness.

Transports via rail are increasing, and major railway infrastructure investments are expected. An important part of this infrastructure is the railway power supply system (RPSS). Future railway power demands are not known. The more distant the uncertain future, the greater the number of scenarios that have to be considered. Large numbers of scenarios make time-demanding (some minutes, each) full simulations of electric railway power systems less attractive and simplifications more so. The aim, and main contribution, of this paper is to propose a fast approximator that uses aggregated traction system information as inputs and outputs. This approximator can be used as an investment planning constraint in the optimization. It considers that there is a limit on the intensity of the train traffic, depending on the strength of the power system. This approximator approach has not previously been encountered in the literature. In the numerical example of this paper, the approximator inputs are the power system configuration; the distance between a connection from contact line to the public grid, to another connection, or to the end of the contact line; the average values and the standard deviations of the inclinations of the railway; the average number of trains; and their average velocity for that distance. The output is the maximal attainable average velocity of an added train for the described railway power system section. The approximator facilitates studies of many future railway power system loading scenarios, combined with different power system configurations, for investment planning analysis. The approximator is based on neural networks. An additional value of the approximator is that it provides an understanding of the relations between power system configuration and train traffic performance. © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20110303

Vision-based vehicle speed measurement (VSM) is one of the most convenient methods available in intelligent transportation systems. Existing methods use an uncalibrated camera to measure vehicle speed, but they do not consider the possibility of camera vibration that leads to poor measurement results. This paper considers the issue when the camera is tilted downward and mounted at a fixed location on a bridge crossing the target street. The camera may vibrate due to wind or bridge movement. A vision-based speed measurement system is described in this paper, along with the vertical-and-horizontal-histogram-based method, which is used to compensate the background of an incoming image. This novel method is utilized to eliminate noise coming from the displacement between an incoming image and a background image that is caused by camera vibration over time. Moreover, a method is presented to automatically detect the vanishing point based on the Hough transform and quadtree. Experimental comparisons of the system to those of the vehicle's own speedometer show that the proposed approach yields a satisfactory estimate of vehicle speed.

This paper presents a comparative study of two surface-mounted permanent-magnet synchronous machines (PMSMs): the first with integral slot windings and the other with fractional slot windings. These machines have the same winding distribution on the stator and the same magnet volume on the rotor but different rotor pole numbers. The objective is to give the advantages of PMSMs with fractional slot windings. This paper also presents a computation method of average copper losses, including the flux weakening and that of average iron losses during the driving cycle for a hybrid electric vehicle (HEV). In this paper, in the electrical motorization of a truck, the specification characteristics give a maximum torque of 500 Nm and a maximum speed of 3000 returns per minute (rpm). Finally, a comparative study in terms of average losses during the driving cycle of the HEV has been presented. The energetic efficiency of the electric motor in the vehicle is shown.

Wireless networks in an open environment are exposed to various large region threats, e.g., natural disasters and malicious attacks. Available works with regard to region failures generally adopt a kind of “deterministic” failure models, which failed to reflect some key features of a real region failure. In this paper, we provide a more general “probabilistic” region failure model to capture the key features of a region failure and apply it for the reliability assessment of wireless mesh networks. To facilitate such an assessment, we develop a grid-partition-based scheme to estimate the expected flow capacity degradation from a random region failure. We then establish a theoretical framework to determine a suitable grid partition such that a specified estimation error requirement is satisfied. The grid partition technique is also useful for identifying the vulnerable zones of a network, which can guide network designers to initiate proper network protection against such failures. This paper helps us understand the network reliability under a region failure and facilitates the design and maintenance of future highly survivable wireless networks.

A novel linear magnetic levitated actuator using the switched reluctance principle is addressed in this paper. This actuator can be applied to precise motion control of automation machines. The proposed system has the advantages of a simple and robust structure, and direct drive capability. The contactless structure eliminates mechanical wear, friction, noise, and heat generation. To verify the feasibility of the proposed system, the magnetic levitated force is analyzed by magnetic circuit analysis (MCA) and by finite-element analysis (FEA). A prototype structure is fabricated, and experiments are performed with the actual hardware. Results of the MCA and the FEA are both compared with the results obtained from the hardware experiments. They all agree with the proposed design methodology. This paper can form a useful reference in the design of a mechanical structure for magnetic levitated switched reluctance actuators.

Joint transmitter–receiver optimization in generalized multicarrier code-division multiplexing (GMC-CDM) systems is investigated in this paper. The optimization consists of a one-tap post-frequency-domain equalizer (post-FDE) and a one–tap pre-FDE. While the one-tap post-FDE is optimized under the criterion of minimum mean square error (MMSE), the one-tap pre-FDE is achieved through three stages of optimization, which are operated at different levels and motivated to achieve, possibly, different objectives, including maximum throughput and maximum reliability. Specifically, in our three-stage pre-FDE, the first-stage pre-FDE is operated at the symbol level, concerning only the symbols within a group. The second-stage pre-FDE is carried out at the group level for harmonization among the groups. Finally, the third-stage pre-FDE handles group partition. In this paper, the error and throughput performance of the GMC-CDM systems is investigated when assuming communications over frequency-selective Rayleigh fading channels. It can be shown that the reliability or throughput of the GMC-CDM systems can be significantly improved by employment of the proposed pre- and post-FDE schemes. Furthermore, the pre- and post-FDE algorithms obtained can be implemented with high flexibility, which facilitates a GMC-CDM system to achieve a good tradeoff between its throughput and reliability.

The main advantage of asymmetrical multilevel inverters is the optimization of levels with a minimum number of power supplies. However, this optimized multilevel system still needs a large number of isolated and floating dc supplies, which makes these converters complicated to implement in electric vehicles (EVs), because the system will require many independent battery packs. In this paper, a very simple scheme, based on a small and cheap high-frequency link (HFL), allows the utilization of only one power supply for the complete multilevel inverter drive, with an inherent regulation of the voltages supplied among the H-bridges. It also allows voltage control with the full number of levels if the dc source is of a variable voltage characteristic. This paper is focused on a 27-level asymmetric inverter, but the strategy, using only one power supply, can be applied to converters with any number of levels. In particular, an asymmetrical 27-level converter needs nine isolated power supplies, and the proposed system reduces these nine sources to only one: the battery car. The topology also permits full regenerative braking working as a three-level converter. The proposed system is intended for application in EVs from power ratings up to 150 kW. Simulations and experimental results show the feasibility to implement this “one-source” multilevel system.

Wireless sensor networks (WSNs) are widely used for various applications. In some applications, it is very likely that the number of sensors is limited, the initial deployment is random, and deployment “holes” (i.e., subareas where there is no sensor) may exist. Therefore, a major challenge in WSNs is to improve the network coverage. A viable solution is to enhance some sensors with mobility capability so that they can move inside the WSNs after the initial deployment, which is referred to as mobile sensor redeployment. In this paper, we target at a generic framework for the optimal mobile sensor redeployment problem in WSNs. In particular, in this paper, the area of a WSN is partitioned into a number of grids, and the gap of each grid is defined as the difference of the number of sensors in the grid from the desired number of sensors. Then, the mobile sensor redeployment problem is formulated as an optimization problem with three optimization requirements: to minimize the sum of gaps of all grids, to minimize the Lp-norm (1 ≤ p ≤ ∞) of the gap vector (where Lp-norm represents a family of optimization objectives when p takes different values), and to minimize the total movement cost of all mobile sensors. Bipartite matching-based redeployment (BMrD) algorithms are provided to solve the optimization problems with different values of p. In this paper, the framework is generic for mobile sensor redeployment because 1) the mobility capabilities of the sensors, the initial sensor distribution, the movement cost measures, and the sensor types are all arbitrary; 2) the coverage requirements in different grids can be heterogeneous; and 3) the BMrD algorithms are generic for different p values. The effectiveness of the BMrD algorithms is validated through theoretical proofs and extensive simulations.

This paper presents a novel batteryless wireless sensor that can be embedded in the road and used for the measurement of traffic-flow rate. Compared with existing inductive loop-based traffic sensors, the new sensor is expected to provide increased reliability, easy installation, and low cost. The sensor requires no external power source and has zero idle power loss. Energy to power this sensor is harvested from the short-duration vibrations that result when an automobile passes over the sensor. Since much of the earlier work in literature on vibration energy harvesting has focused on continuous sources of vibration, this paper focuses on short-duration vibrations and on developing low-power control algorithms that can be implemented on the sensor using an analog circuit. To this effect, this paper develops and compares three control algorithms: 1) “fixed threshold switching,” 2) “maximum voltage switching,” and 3) “switched inductor.” The “switched inductor” algorithm is shown to be the most effective at maximizing harvested energy. Experimental results are presented and validate the fact that adequate energy can be harvested from each passing vehicle to enable successful wireless transmission of traffic data.

The estimation of the frictional and clamping forces is one of the key issues in the design and implementation of the electromechanical brake (EMB) system. In this paper, a clamping-force control algorithm is presented along with a consideration of the frictional characteristics and the estimation of the clamping force for a planetary reduction gear-type EMB. The frictional model is developed by including the frictional effect of the motor, the planetary gear, and the screw thread. Since the clamping-force estimation requires the distance of the contact gap between the pad and the disk, an initial gap-distance control algorithm that uses the gradient change of the motor torque is proposed. This paper is concluded with a discussion of the performance of the control algorithm by comparing the simulation results with the experimental results.

Hybrid electric vehicle (HEV) technology has numerous advantages over conventional vehicles, from standpoints of fuel economy, energy independence, and environmental concerns. Effective solutions for HEVs have been expanding their applications over highway vehicles, such as sedans and sport utility vehicles, into a variety of traditional vehicles. HEV systems applied to off-highway heavy-duty vehicles, which are operated by an engine, a generator, and traction motors, are investigated in this paper. This paper explores the use of a direct ac/ac converter for off-highway heavy-duty HEVs, which can directly drive traction motors from the generator with no intermediate dc conversion. In addition, a phase-redundant matrix converter structure with a backup leg and a control scheme is proposed to guarantee reliable and safe vehicle operations by providing continuous disturbance-free operations against converter faults. Fault-diagnosis techniques using line-to-line and phase voltages are presented not only to detect system malfunctions but to locate a failed switching device among 18 switching components as well. Appropriate reconfiguration structure and control actions with accurate knowledge about fault occurrence can avoid propagation of fault, which may lead to a catastrophic system failure.

The fuel economy and all-electric range (AER) of hybrid electric vehicles (HEVs) are highly dependent on the onboard energy-storage system (ESS) of the vehicle. Energy-storage devices charge during low power demands and discharge during high power demands, acting as catalysts to provide energy boost. Batteries are the primary energy-storage devices in ground vehicles. Increasing the AER of vehicles by 15% almost doubles the incremental cost of the ESS. This is due to the fact that the ESS of HEVs requires higher peak power while preserving high energy density. Ultracapacitors (UCs) are the options with higher power densities in comparison with batteries. A hybrid ESS composed of batteries, UCs, and/or fuel cells (FCs) could be a more appropriate option for advanced hybrid vehicular ESSs. This paper presents state-of-the-art energy-storage topologies for HEVs and plug-in HEVs (PHEVs). Battery, UC, and FC technologies are discussed and compared in this paper. In addition, various hybrid ESSs that combine two or more storage devices are addressed.

In this paper, we propose an analysis of frequency rendezvous techniques employing three different scanning rules by combining analytical results with computer simulations. Frequency rendezvous is a critical step in bootstrapping a wireless network that does not possess centralized control. Current techniques for enabling frequency rendezvous in decentralized dynamic spectrum access (DSA) networks either require preexisting infrastructure or use one of several simplifying assumptions regarding the architecture, such as the use of regularly spaced frequency channels for communications. Our approach is designed to be operated in a purely decentralized wireless networking environment, where no centralized control is present, and the spectrum possesses no predefined channels. This is accomplished via a combination of receiver pilot tones, a tone-scanning protocol, and a transmitter/receiver handshaking process. To realize a shortest search time for the target receiver, an efficient scanning rule should be employed. In this paper, three scanning rules, i.e., frequency sequence scanning, pilot tone strength scanning, and cluster scanning, are analyzed using mathematical derivations. To validate our theoretical result, we test the three scanning rules with computer simulations.

In this paper, we investigate the net sidelobe power reduction of noncontiguous orthogonal frequency-division-multiplexing (NC-OFDM) signals using an approach combining cancellation carriers (CCs) and modulated filter banks (MFBs). NC-OFDM can enable high-speed dynamic spectrum access (DSA) networks via transmission over several disjoint separate frequency bands. However, OFDM generally produces a substantial amount of out-of-band (OOB) interference that can potentially disrupt communications in adjacent wireless channels. One solution is to apply a filter bank, which is an array of bandpass filters that serves to isolate different frequency components of a signal. In this paper, we propose a combined OFDM sidelobe-suppression approach consisting of MFBs and the existing CC technique to achieve OOB radiation reduction. The simulation results show a significant net reduction of sidelobe power after using these two techniques. Furthermore, an algorithm has been developed to determine the number of OFDM data carriers (DCs) that can be transmitted in a given spectrum space.

This paper investigates the network resource allocation in multiuser downlink wireless systems where the base station and the mobile stations are equipped with multiple antennas to provide fair and efficient transmission services to the mobile users. We focus on packet scheduling, given that it has a significant impact on the overall performance of a multiple-input-multiple-output (MIMO) system. Most previous schedulers designed at the packet level do not take into account the traffic characteristics (different packet lengths and the arrival process parameters); consequently, they fall short of simultaneously providing fairness and a low average packet transmission delay. We are making use of a flexible packet transmission algorithm at the medium access control (MAC) layer to develop and propose a novel scheduler, which is referred to as MIMO packet-based proportional fairness (MP-PF). The new scheduler is designed with the goal of providing high performance in terms of a low average packet transmission delay and time and service fairness among the users based on the concept of proportional fairness. The scheduler also conserves work and takes into consideration the packet length, the user queue length, the user transmission rate (related to its channel quality), and the service guarantees for heterogeneous users. The well-known ideal service fair scheduler called max-min can also significantly be improved using our framework by taking into consideration the traffic characteristics. We also provide an analysis for the fairness of the new scheduler in terms of time and service allocation, which is the key contribution of this paper. Simulations that consider the traffic characteristics and the mobility of users show the relatively low average packet transmission delay and demonstrate the time and service fairness capabilities of MP-PF, compared with other well-known MIMO schedulers.

This paper presents three criteria for evaluating the motoring operations of switched reluctance motor (SRM) drives for electric vehicles (EVs). They imply motoring torque, copper loss, and torque ripple, respectively. The effects of the turn-off and turn-on angles on these criteria are investigated under hysteresis current control. To fulfill the best motoring operation, consequently, the multiobjective optimization function is developed by using three weight factors and three groups of base values: the correct balance between the maximum average torque, the maximum average torque per root mean square current, and the maximum torque smoothness factor. The study in this paper shows that the turn-off and the turn-on angles can be optimized to maximize the developed multiobjective function. In addition, the control method for the best motoring operation of SRM drives in EVs is proposed. In this method, two angular controllers are proposed to automatically tune the turn-off and turn-on angles to obtain high motoring torque, low copper loss, and low torque ripple. Simulations and experimental results have demonstrated the proposed optimal control method. Therefore, this paper offers a valuable and feasible approach for implementing the best motoring operation of SRM drives for EVs.

The distribution of the interservice time, which is the interval between the end of a call served and the start of the succedent call served by a portable, is a crucial parameter for modeling and cost analysis for location management in personal communication service (PCS) networks. The interservice time differs from the interarrival time due to the busy-line effect. However, in the literature, most of the cost analyses for location management were carried out by ignoring the busy-line effect, i.e., by identifying the interservice time with the interarrival time, because, so far, there is no analytical result for the interservice time distribution considering the busy-line effect. In this paper, we develop an analytical model to investigate the busy-line effect on the interservice time distribution. Closed-form analytical formulas for the interservice time are derived. A numerical study shows that a big discrepancy exists between the interarrival time and the interservice time. Based on the analytical results for the interservice time, the impact of the busy-line effect on modeling of portable movements in PCS networks is further evaluated. An analytical result for the distribution of the number of cell-boundary crossings during the interservice time is obtained. Both analytical results and numerical examples indicate that the busy-line effect has influence on the distribution of the number of cell-boundary crossings during the interservice time. Therefore, cost analysis for location management without considering the busy-line effect may lead to unreliable results. The results presented in this paper pave the way for modeling location management and portable movements in PCS networks.

The development of delay-tolerant networks (DTNs) has attracted significant attention in the network research community. In this paper, we propose a new type of DTN - a homing-pigeon-based DTN (HoP-DTN). In the HoP-DTN, each node owns a dedicated messenger (called a pigeon). The only form of internode communication is for a pigeon to periodically carry a batch of messages originated at the home node, deliver them to the corresponding destination nodes, and return home. Clearly, given message-expiration times, some messages may not reach their destinations by the deadline. Through analysis and simulations, we study the relationship between key parameters of the system, including average message delay, expiration time, delivery ratio, arrival rate, and batch size of messages. Various simulations have been conducted to demonstrate the accuracy of our analysis. Our theoretical study and simulations present a deep insight into the characteristics of the proposed system. Some interesting observations from simulations are discussed in detail in this paper, and the results demonstrate that our proposed scheme performs better in terms of average message delay, message-delivery ratio, and cost-effectiveness.

In this paper, we propose a transmitter-based linear-precoding scheme that outperforms conventional precoding by making use of a portion of the interference between the users in a code-division multiple-access (CDMA) system downlink. The utilization of part of the interference is achieved by selectively orthogonalizing the desired symbols to destructive interference by means of precoding while allowing interference that constructively contributes to the useful signal's energy. The existence and exploitation of constructive interference effectively spreads the signal constellation and enhances the signal-to-interference-plus-noise ratio (SINR) at the receiver. SINR improvement is attained with no need for additional power-per-user investment at the transmitter since energy that is inherent in the CDMA system is utilized. The scheme introduced in this paper applies to the downlink of cellular phase-shift keying (PSK)-based CDMA systems. Theoretical analysis and comparative simulations show that significant performance improvement can be attained with the proposed technique.

In Sen and Matolak's earlier paper, 5-GHz-band vehicle-to-vehicle (V2V) channel models were presented for channel bandwidths of 5 and 10 MHz. In this paper, we provide additional tapped delay line models for bandwidths of 1, 20, 33.33, and 50 MHz based upon the data used in Sen and Matolak's paper. We provide tables of channel parameters for five types of V2V channel classes and also include example tap correlation coefficients. Root-mean-square delay spread values are summarized, as are values of bandwidth for which the channel frequency correlation takes values of 0.7 and 0.5. As with the results from Sen and Matolak's paper, these models should be useful for designers in future V2V communication systems.

In IEEE Standards 802.16e (air interface standard for MWiMAX) and 802.16m (evolution of MWiMAX for IMT-Advanced), power saving is one of the important issues for battery-powered mobile stations (MSs) due to mobility. According to the IEEE 802.16e standard, when an MS switches from awake mode to sleep mode, the MS is required to send a sleep request (MOB-SLP-REQ) message and to receive a sleep response (MOB-SLP-RSP) message. In this paper, we propose a new sleep mode scheme called the power-saving mechanism with periodic traffic indications, where the MOB-SLP-REQ/RSP messages are omitted, and a traffic indication (TRF-IND) message is periodically sent at the beginning of every constant TRF-IND interval. The merits of the proposed scheme are simple implementation, reduction of energy consumption, and saving of the resource compared with the sleep mode in the IEEE 802.16e standard. The proposed scheme in this paper is well aligned with the design policy of sleep mode in discussion at IEEE 802.16m in the sense that it tries to minimize the state transition overhead between the awake and sleep modes, and hence, it can reduce the delay for state transition and enhance the power-saving efficiency. We investigate the performance of the proposed scheme in two ways: simulation and analytical methods. Using the performance evaluation, we find the optimal TRF-IND interval, which minimizes the average power consumption of the MS while satisfying the quality of service (QoS) on the mean delay. Numerical results show that the proposed scheme has 20%-50% reduction of the energy compared with the power-saving class (PSC) of type I, which is one of three operations for sleep mode in IEEE 802.16e.

The IEEE 802.16j standard has been developed to provide performance enhancement to the existing IEEE 802.16e network by incorporating the multihop relay (MR) technology. However, frequent handoffs and low spectrum-utilization issues that were not encountered in IEEE 802.16e may be incurred in IEEE 802.16j. The relay station (RS) grouping is one optional mechanism in the IEEE 802.16j MR standard to overcome these problems. The concept of RS grouping is to group neighboring RSs together to form an RS group, which can be regarded as a logical RS with larger coverage. In this paper, we investigate RS grouping performance enhancement in terms of throughput and handoff frequency. This paper designs an RS grouping algorithm to minimize handoffs by utilizing a greedy grouping policy: RS pairs with higher handoff rates will have higher priority for selection. The simulation results show that the handoff frequency of the considered MR network can significantly be reduced, and suitable RS grouping patterns can be derived using our grouping algorithm. In addition, we propose two centralized scheduling policies, i.e., the throughput-first (TF) policy to maximize the system throughput and the delay-first (DF) policy to minimize the average packet delay. By integrating our RS grouping algorithm and centralized scheduling algorithms, the simulation results indicate that, for the case of fixed users, groupings with smaller group sizes can result in better throughput performance. However, when user mobility is considered, the throughput value increases as the group size increases. Furthermore, we also show that the DF policy can both minimize the average packet delay and provide the fairness property among users with different traffic loads.

In this paper, we analyze a hybrid electric vehicle structure and propose a simple and computationally cheap yet close-to-optimal energy-management strategy. The underlying hybrid configuration is of parallel type. Furthermore, the parallel hybrid does not include a clutch between the electric motor and the engine. The considered vehicle uses a six-speed dual-clutch transmission (DCT). The proposed supervisory controller considers both the torque split management and the gear-shifting strategy. Results show that the proposed approach achieves fuel consumption (FC) within 1% of the global optimum for most driving cycles. In addition, using the proposed controller, the number of gears in the gearbox can be reduced to three while maintaining the FC within 2% of what is achieved with a six-speed gearbox. Moreover, the results shown in this paper are not sensitive to limitations and energy losses associated with gear shifting.

A mobile sensor is used to cover a number of points of interest (PoIs), where dynamic events appear and disappear according to the given random processes. The sensor, which is of sensing range r, visits the PoIs in a cyclic schedule and gains information about any event that falls within its range. We consider the temporal dimension of the sensing as given by a utility function, which specifies how much information is gained about an event as a function of the cumulative sensing or observation time. The quality of monitoring (QoM), i.e., the fraction of information captured about all events, depends on the speed of the sensor and has been analyzed in an earlier paper for different utility functions. The prior work, however, does not consider the energy of motion, which is an important constraint for mobile sensor coverage. In this paper, we analyze the expected Information captured Per unit of Energy consumption (IPE) as a function of the event type (in terms of the utility function), the event dynamics, and the speed of the mobile sensor. Our analysis uses a realistic energy model of motion, and it allows the sensor speed to be optimized for information capture. The case of multiple sensors will also be discussed. Extensive simulation results verify and illustrate the analytical results.

Directional sound can be used to provide warnings to specific vehicles without disturbing other vehicles on the highway. An example of such an application is the need to alert a vehicle that is likely to intrude into a highway construction work zone. Long-distance auditory warnings potentially reduce the time for the driver to visually locate the work zone. This paper reviews the currently available technologies that can potentially be used to develop a long-distance auditory warning system for highway work-zone applications. Of these, ultrasound-based parameter arrays and time-delay-controlled arrays of compact ordinary speakers are taken up for detailed analysis and experimental evaluation. An ultrasound-based parametric array is found to be effective at generating highly directional sound. However, when issues of cost, installation, maintenance, and price are considered, the more suitable technology for work zones is found to be arrays of flat-panel loudspeakers with time delay control. Such a system is inexpensive and can be used to effectively generate directional sound for long-distance auditory warnings. This paper shows that an annular pattern of flat-panel speakers can provide directional sound along a highway lane, with no real-time control of time delay necessary. Hence, an extremely inexpensive and portable system can be obtained, with components consisting of compact flat-panel speakers, a battery, power supply, and inexpensive electronics. In terms of performance, the developed system can provide a difference in the sound level of 6 dB or higher between adjacent lanes at all frequencies in the range of 2-4 kHz at distances of up to 40 m from the location of the warning system.

Online estimation of the noise floor is essential for the accurate scheduling of wideband code-division multiple-access (WCDMA) enhanced uplink (EUL) channel transmissions. The noise floor is used for computation of the load of the uplink of the cell, which is then used to compute the momentary headroom available for EUL traffic. This paper proves a result on Kalman filter scaling, which significantly extends the dynamic range of a previous noise-floor-estimation scheme. This paper proceeds by proving that an optimal Bayesian minimum estimator can be written in recursive form using geometric-rather than arithmetic-averaging. As compared with previous algorithms, the recursive scheme reduces the memory requirement without compromising performance, at the same time that the tracking properties are enhanced.

Auto rickshaws are three-wheeled vehicles that are extensively used in many Asian countries as taxis of people and goods. Although the vehicle design is well suited to the environment in which it operates, it is a crude and inefficient design. Due to poor vehicle maintenance and the use of inefficient two- or four-stroke engines with very little pollution control, auto rickshaws present a grave pollution problem in major Indian cities. This paper details the overall development of an advanced solar-assisted electric auto rickshaw. Research on the conventional auto rickshaw is presented, as well as future conceptual infrastructure designs for electric rickshaws and the recent design research, simulations, and experimental validation of the next auto rickshaw. The proposed solar/battery electric three-wheeler is meant to match and exceed the conventional vehicle's performance but with a more intelligent and efficient design. We introduce the next overall design of the rickshaw in this paper as Auto Rickshaw 2.0, where the conventional vehicle is version 1.0. The technical development aim for Auto Rickshaw 2.0 is to decrease the total electric power needed for propulsion with an optimized battery system and a more efficient motor and inverter. Four system drive-train options are covered, a rickshaw prototype is built, and several configurations are simulated and analyzed in the Advanced Vehicle Simulator (ADVISOR) software. Additionally, conceptual infrastructure designs are modeled and optimized in the Hybrid Optimization Model for Electric Renewables (HOMER) software.

The performance of IEEE 802.11 wireless local area networks (WLANs) is affected by the channel conditions of wireless medium and the contention processes of wireless stations. Under these effects, it is feasible to adjust the frame size to maximize the throughput. The majority of existing frame-size optimization solutions are based on the assumption that the optimal frame size only depends on the channel conditions. These approaches do not consider the contention effects, thus leading to suboptimal solutions. In this paper, we tackle the frame-size optimization problem using a machine-learning-based adaptive approach. This approach takes both the channel conditions and the contention effect into consideration. In this approach, each source station performs the throughput measurement and collects the ldquoframe size-throughputrdquo patterns. The collected patterns contain the knowledge about the effects of channel conditions and contention processes. Based on these patterns, our approach uses neural networks to accurately model the throughput as a function with respect to the frame size. After the knowledge building, we obtain the gradient information to adjust the frame size. The main contribution of this paper is that we take both the channel conditions and the contention effect into consideration, without any assumptions of the channel models or the stations' behavior that are required by the previous analytical solutions. We perform comprehensive simulations to validate that the proposed approach can effectively optimize the frame size under various channel conditions and contention effects. We also implement the proposed approach and perform comprehensive experiments on a real testbed to evaluate the effectiveness and reaction speed of the proposed approach in practice.

Current approaches for designing wireless mesh networks (WMNs) suffer from low-end-to-end-throughput performance. This disadvantage mainly comes from the traffic aggregation and multihop properties of WMNs. Although the throughput performance can be improved by utilizing multiple channels and multiple radios, the knowledge of how good the performance can be is still unavailable. Some previous works endeavored to heuristically improve the systems' performance, while others focused on the optimization algorithms for satisfying the clients' traffic demand. There is no work, until now, that can provide the knowledge of the system capacity. Although optimization algorithms have been proposed in previous papers, they require the exact traffic load input and make the ldquooptimalrdquo result easily outdated due to local topology and traffic changes. In this paper, we investigate the capability that WMNs can offer the mesh clients to deliver/receive data across the gateways, which is termed the portal capacity. Furthermore, we propose our solution to achieving the optimality in portal capacity through the centralized algorithm while retaining optimality via distributed tuning when local changes in either topology or traffic occur in the system. The concept of portal capacity provides us with very useful information about a WMN's capability, which can facilitate the optimization of the end-to-end throughput and fairness. In addition to this, this paper is the first one that takes the optimality and dynamic property of the system into consideration.

In this paper, we investigate the power and rate-control schemes for multiple cognitive radio (CR) links in the same neighborhood, which operate over multiple channels (frequency bands) in the presence of licensed primary radios (PRs) with a delay constraint imposed on data transmission. By further considering a practical delay in spectrum sensing, an efficient algorithm is proposed to maximize the average sum rate of the CR links over a finite time horizon under the constraints on the CR-to-PR interference and the average transmit power for each CR link. In the proposed algorithm, the PR occupancy of each channel is modeled as a discrete-time Markov chain (DTMC). Based on such a model, a novel power and rate control strategy based on dynamic programming (DP) is derived, which is a function of the delayed spectrum sensing output, the instantaneous channel gains for the CR links, and the remaining power budgets for the CR transmitters. Simulation results show that the proposed algorithm leads to a significant performance improvement over three heuristic algorithms discussed in this paper.

This paper proposes a new intelligent transportation system (ITS) that uses not only integrated cellular and wireless multihop relaying technologies but vehicles' mobility profiles to provide quality yet affordable services as well. It focuses on a subsystem where cellular bandwidth is mostly used for control signals, and a wireless mesh network called ad hoc distribution network (ADN) is used for file transfer in a multihop fashion from one or more server stations to vehicles via access points (APs) using ad hoc channels. A major design goal is to maximize the amount of requested data that can be delivered to the requesting vehicles during their journey using the ADN, taking into consideration the limited coverage of each AP and the requirement that the requested data have to arrive at a certain AP before the requesting vehicles arrive at that AP in order for the data to be downloadable. This paper proves that the optimization problem, as well as its key variations, is NP-hard and proposes efficient solutions to the problem. Analysis and realistic simulations involving a real city map and practical vehicular traces are used to evaluate the performance, and the results indicate that satisfying performance for file download applications can be achieved.

This paper presents and analyzes a method for enhancing the privacy of vehicles that use the public-key infrastructure (PKI) to secure communications. In particular, it examines the privacy limitations of a PKI system, where certificates are shared among multiple vehicles using a combinatorial certificate scheme. Such a system was implemented in the U.S. Vehicle Infrastructure Integration (VII) proof-of-concept trial to secure vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication and preserve vehicle privacy. The analysis shows that, in low vehicle densities, there is a high probability that a vehicle may have a locally unique certificate that is not shared by other vehicles. Vehicles using unique certificates may be vulnerable to being tracked or identified. This paper proposes a vehicle-based certificate-selection method for enhancing the privacy of vehicle communications. In our method, a vehicle monitors the certificates in use by neighboring vehicles and identifies those certificates that it also possesses. The vehicle then selects a certificate already in use to secure its own communication. This allows a vehicle to ldquoblend inrdquo to its environment but without substantially increasing an attacker's ability to evade exposure. We provide an analysis of the anonymity and unlinkability properties of the method and demonstrate that it rapidly reduces the number of vehicles using unique certificates to increase privacy.

Combining high-energy-density batteries and high-power-density ultracapacitors in fuel cell hybrid electric vehicles (FCHEVs) results in a high-performance, highly efficient, low-size, and light system. Often, the battery is rated with respect to its energy requirement to reduce its volume and mass. This does not prevent deep discharges of the battery, which are critical to the lifetime of the battery. In this paper, the ratings of the battery and ultracapacitors are investigated. Comparisons of the system volume, the system mass, and the lifetime of the battery due to the rating of the energy storage devices are presented. It is concluded that not only should the energy storage devices of a FCHEV be sized by their power and energy requirements, but the battery lifetime should also be considered. Two energy-management strategies, which sufficiently divide the load power between the fuel cell stack, the battery, and the ultracapacitors, are proposed. A charging strategy, which charges the energy-storage devices due to the conditions of the FCHEV, is also proposed. The analysis provides recommendations on the design of the battery and the ultracapacitor energy-storage systems for FCHEVs. Udgivelsesdato: October 2 Combining high-energy-density batteries and high-power-density ultracapacitors in fuel cell hybrid electric vehicles (FCHEVs) results in a high-performance, highly efficient, low-size, and light system. Often, the battery is rated with respect to its energy requirement to reduce its volume and mass. This does not prevent deep discharges of the battery, which are critical to the lifetime of the battery. In this paper, the ratings of the battery and ultracapacitors are investigated. Comparisons of the system volume, the system mass, and the lifetime of the battery due to the rating of the energy storage devices are presented. It is concluded that not only should the energy storage devices of a FCHEV be sized by their power and energy requirements, but the battery lifetime should also be considered. Two energy-management strategies, which sufficiently divide the load power between the fuel cell stack, the battery, and the ultracapacitors, are proposed. A charging strategy, which charges the energy-storage devices due to the conditions of the FCHEV, is also proposed. The analysis provides recommendations on the design of the battery and the ultracapacitor energy-storage systems for FCHEVs.

A software-defined radio (SDR) for ultrawideband (UWB) communication systems places several stringent requirements on the analog-to-digital converter (ADC). One alternative to using a single ADC is to sample the received signal with an array of lower speed ADCs that were driven by interleaved sampling clocks; however, mismatches among the ADCs will result in signal distortion. This paper makes three important contributions to overcoming this problem: 1) analytical quantification of the impact of ADC gain, offset, and timing mismatches on the performance of a time-interleaved sampling ADC array for UWB signals; 2) demonstration of the efficacy of using a pilot-based matched-filter architecture to mitigate the impact of timing mismatches in the presence of multipath; and 3) implementation of an 8-ADC time-interleaved UWB SDR testbed that operates at an effective sampling frequency of 6.4 GHz. In addition, our findings allow for the design specification of the number of pilots required to obtain a desired system performance. The simulation and measured performance results from this paper demonstrate that ADC mismatches can be controlled to within plusmn10%, yielding acceptable levels of distortion and bit-error-rate (BER) performance on the UWB SDR testbed. Both analytical and simulation results also demonstrate the efficacy of a pilot-based matched filter in mitigating the impact of timing mismatch errors, even in the presence of multipath.

Most methods for state-of-charge or state-of-health prognostics are impedance based. Impedance models must be as simple as possible to be implemented on embedded applications but as accurate as possible to represent the main electrochemical phenomena. The parameters of such models can be identified using impedance spectroscopy. However, the electrochemical features change in relation to numerous parameters, such as temperature or aging, which involves updating the model of the battery online. This paper deals with the use of an extended Kalman filter (EKF) for the observation of the parameters of a Li-ion battery lumped model. First, this paper will focus on the electrical model that can be used to represent the main electrochemical phenomena in the battery. Then, mathematical considerations about the EKF are reminded to be applied to the observation of the impedance parameters of the battery. This method has been validated on an urban driving cycle of a hybrid electric vehicle.

In this paper, we propose and investigate a relay-diversity transmission scheme for the direct-sequence code-division multiple-access (DS-CDMA) downlink, where each (destination) mobile terminal (MT) is aided by a cluster of relays to achieve the relay diversity. In the considered system, downlink multiuser interference (MUI) is suppressed with the aid of transmitter preprocessing operated at the base station (BS). Two transmitter preprocessing schemes are considered, which are operated in the principles of transmitter zero forcing (TZF) and transmitter minimum mean square error (TMMSE). At the MTs, signals received from the BS and relays are combined based on the principles of maximal ratio combining (MRC) or maximum signal-to-interference-plus-noise ratio (MSINR). In this paper, the bit-error-rate (BER) performance of the relay-assisted DS-CDMA downlink is investigated when the communication channels are assumed to experience both propagation path loss and generalized Nakagami- m fading. Our study and simulation results show that the transmitter preprocessing can help to achieve the relay diversity by efficiently mitigating the MUI present at the relays and MTs. Furthermore, in our proposed relay-diversity scheme, the relays only require low-complexity signal processing to forward information to their served MTs.