The focus of this paper is on the rate and power control algorithms in Dedicated Short Range Communication (DSRC) for vehicular networks. We first propose a utility maximization framework by leveraging the well-developed network congestion control, and formulate two subproblems, one on rate control with fixed transmit powers and the other on power control with fixed rates. Distributed rate control and power control algorithms are developed to solve these two subproblems, respectively, and are proved to be asymptotically optimal. Joint rate and power control can be done by using the two algorithms in an alternating fashion. The performance enhancement of our algorithms compared with a recent rate control algorithm, called EMBARC, is evaluated by using the network simulator ns2.
The design of rate and power control algorithms in DSRC is one of most critical problems in ITS. Error Model Based Adaptive Rate Control (EMBARC) @cite_15 is a recent rate control protocol which integrates several existing rate control algorithms including the Linear Integrated Message Rate Control (LIMERIC) @cite_16 , Periodically Updated Load Sensitive Adaptive Rate control (PULSAR) @cite_0 , and the InterVechicle Transmission Rate Control (IVTRC) @cite_19 . LIMERIC allocates the wireless channel equally among all vehicles that share the same bottleneck link while guaranteeing the channel load is below a given threshold. IVTRC generates messages and adapts transmission probabilities based on the Suspected Tracking Error (STE) calculated based on vehicle dynamics to avoid collisions. In EMBARC, the message rates are controlled by LIMERIC and are further modified to satisfy the STE requirement.
@cite_0 @cite_19 @cite_15 @cite_16
2002719705 2110426163 2071515504 2038940887
Channel congestion is one of the major challenges for deployment of collision avoidance systems based on DSRC (Dedicated Short Range Communication) in large scale networks. If vehicles do not adapt to congestion conditions, DSRC transmissions could encounter extensive packet losses in areas of high vehicle density, leading to degradation in the performance of safety applications. In this paper, we propose a novel congestion control algorithm called Error Model Based Adaptive Rate Control (EMBARC) which adapts a vehicle's transmission rate as a function of channel load and vehicular dynamics. In particular, we extend Linear Integrated Message Rate Control (LIMERIC) algorithm's message rate adaptation with the capability to preemptively schedule messages based on the vehicle's movement. This leads to more transmission opportunities for vehicles with higher dynamics. The determination of a preemptive scheduling event is based on a novel suspected tracking error technique. Since LIMERIC maintains the channel load around a specific value, vehicles moving less dynamically will adapt to slightly reduced transmission rates in EMBARC. The extra transmit opportunities for highly dynamic vehicles reduce incidences of large tracking error compared to a pure LIMERIC approach. At the same time, EMBARC's use of adaptive rate control provides tracking error advantages over systems that transmit largely independent of channel load. We use simulations of a road with a winding segment to compare EMBARC with algorithms that do not take both channel load and vehicle dynamics into account. The results show that EMBARC has the best tracking accuracy among these algorithms over a wide range of node densities. Wireless vehicle-to-vehicle (V2V) and vehicle-toinfrastructure (V2I) communication holds great promise for significantly reducing the human and financial costs of vehicle collisions. A common characteristic of this communication is the broadcast of a device's core state information at regular intervals (e.g., vehicle speed and location or traffic signal state and timing). Unless controlled, the aggregate of these broadcasts will congest the channel under dense traffic scenarios, reducing the effectiveness of collision avoidance applications that use transmitted information. Active congestion control using distributed techniques is a topic of great interest for establishing the scalability of this technology. This paper defines a new adaptive congestion control algorithm that can be applied to the message rate of devices in this vehicular environment. While other published approaches rely on binary control, the LInear MEssage Rate Integrated Control (LIMERIC) algorithm takes advantage of full-precision control inputs that are available on the wireless channel. The result is provable convergence to fair and efficient channel utilization in the deterministic environment, under simple criteria for setting adaptive parameters. This “perfect” convergence avoids the limit cycle behavior that is inherent to binary control. We also discuss several practical aspects associated with implementing LIMERIC, including guidelines for the choice of system parameters to obtain desired utilization outcomes, a gain saturation technique that maintains robust convergence under all conditions, convergence with asynchronous updates, and using channel load to determine the aggregate message rate that is observable at a receiver. This paper also extends the convergence analysis for two important cases, i.e., measurement noise in the input signal and delay in the update process. This paper illustrates key analytical results using MATLAB numerical results and employs standard NS-2 simulations to demonstrate the performance of LIMERIC in several high-density scenarios. Abstract Safety and efficiency applications in vehicular networks rely on the exchange of periodic messages between vehicles. These messages contain position, speed, heading, and other vital information that makes the vehicles aware of their surroundings. The drawback of exchanging periodic cooperative messages is that they generate significant channel load. Decentralized Congestion Control (DCC) algorithms have been proposed to minimize the channel load. However, while the rationale for periodic message exchange is to improve awareness , existing DCC algorithms do not use awareness as a metric for deciding when, at what power, and at what rate the periodic messages need to be sent in order to make sure all vehicles are informed. We propose an environment- and context-aware DCC algorithm combines power and rate control in order to improve cooperative awareness by adapting to both specific propagation environments ( e.g. , urban intersections, open highways, suburban roads) as well as application requirements ( e.g. , different target cooperative awareness range). Studying various operational conditions ( e.g. , speed, direction, and application requirement), ECPR adjusts the transmit power of the messages in order to reach the desired awareness ratio at the target distance while at the same time controlling the channel load using an adaptive rate control algorithm. By performing extensive simulations, including realistic propagation as well as environment modeling and realistic vehicle operational environments (varying demand on both awareness range and rate), we show that ECPR can increase awareness by 20 while keeping the channel load and interference at almost the same level. When permitted by the awareness requirements, ECPR can improve the average message rate by 18 compared to algorithms that perform rate adaptation only. Vehicular ad hoc networks play a critical role in enabling important active safety applications such as cooperative collision warning. These active safety applications rely on continuous broadcast of self-information by all vehicles, which allows each vehicle to track all its neighboring cars in real time. The most pressing challenge in such safety-driven communication is to maintain acceptable tracking accuracy while avoiding congestion in the shared channel. In this article we propose a transmission control protocol that adapts communication rate and power based on the dynamics of a vehicular network and safety-driven tracking process. The proposed solution uses a closed-loop control concept and accounts for wireless channel unreliability. Simulation results confirm that if packet generation rate and associated transmission power for safety messages are adjusted in an on-demand and adaptive fashion, robust tracking is possible under various traffic conditions. Cooperative inter-vehicular applications rely on the exchange of broadcast single-hop status messages among vehicles, called beacons. The aggregated load on the wireless channel due to periodic beacons can prevent the transmission of other types of messages, what is called channel congestion due to beaconing activity. In this paper we approach the problem of controlling the beaconing rate on each vehicle by modeling it as a Network Utility Maximization (NUM) problem. This allows us to formally define the notion of fairness of a beaconing rate allocation in vehicular networks. The NUM model provides a rigorous framework to design a broad family of simple and decentralized algorithms, with proved convergence guarantees to a fair allocation solution. In this context, we propose the Fair Adaptive Beaconing Rate for Intervehicular Communications (FABRIC) algorithm, which uses a particular scaled gradient projection algorithm to solve the dual of the NUM problem. Simulation results validate our approach and show that, unlike recent proposals, FABRIC converges to fair rate allocations in multi-hop and dynamic scenarios. We propose an intervehicle communication framework for the cooperative active safety system (CASS) whose operation is based on the dissemination of each vehicle's state information through a wireless network. Such a CASS requires each subject vehicle to be aware of its surroundings, particularly of the motion and position of other vehicles in its proximity. In this paper, we assume that all vehicles are equipped with onboard communication devices. In such situations, the wireless channel is simultaneously shared by a large number of vehicles, and one of the most difficult challenges in designing CASS is to maintain real-time tracking accuracy of neighboring vehicles while avoiding network congestion and failure. To address this issue, we analyze the problem that multiple scalar linear time-invariant dynamical systems track each other over a multiaccess channel, and then, we propose a rate adaptation algorithm to distributively control the self-information broadcast behavior of each vehicle. The proposed algorithm uses a closed-loop control concept and accounts for the lossy channel. Simulation results show that, if the message generation rate is dynamically adjusted in an on-demand fashion, more accurate and robust tracking performance can be achieved under various traffic conditions. The current framework of network utility maximization for rate allocation and its price-based algorithms assumes that each link provides a fixed-size transmission "pipe" and each user's utility is a function of transmission rate only. These assumptions break down in many practical systems, where, by adapting the physical layer channel coding or transmission diversity, different tradeoffs between rate and reliability can be achieved. In network utility maximization problems formulated in this paper, the utility for each user depends on both transmission rate and signal quality, with an intrinsic tradeoff between the two. Each link may also provide a higher (or lower) rate on the transmission "pipes" by allowing a higher (or lower) decoding error probability. Despite nonseparability and nonconvexity of these optimization problems, we propose new price-based distributed algorithms and prove their convergence to the globally optimal rate-reliability tradeoff under readily-verifiable sufficient conditions. We first consider networks in which the rate-reliability tradeoff is controlled by adapting channel code rates in each link's physical-layer error correction codes, and propose two distributed algorithms based on pricing, which respectively implement the "integrated" and "differentiated" policies of dynamic rate-reliability adjustment. In contrast to the classical price-based rate control algorithms, in our algorithms, each user provides an offered price for its own reliability to the network, while the network provides congestion prices to users. The proposed algorithms converge to a tradeoff point between rate and reliability, which we prove to be a globally optimal one for channel codes with sufficiently large coding length and utilities whose curvatures are sufficiently negative. Under these conditions, the proposed algorithms can thus generate the Pareto optimal tradeoff curves between rate and reliability for all the users. In addition, the distributed algorithms and convergence proofs are extended for wireless multiple-inpit-multiple-output multihop networks, in which diversity and multiplexing gains of each link are controlled to achieve the optimal rate-reliability tradeoff. Numerical examples confirm that there can be significant enhancement of the network utility by distributively trading-off rate and reliability, even when only some of the links can implement dynamic reliability. In Vehicle Safety Communications (VSC) based on IEEE 802.11p, vehicles establish a mutual awareness of their presence by periodically broadcasting status messages, aka beacons. If vehicle density is high and beaconing is not regulated, the channel can become congested, impairing reception performance and safety benefit. As a countermeasure, a number of congestion control approaches have been suggested, adapting transmit (Tx) power, beacon generation rate (Tx rate), or both. However, in general these approaches did not show what the optimal outcome for congestion control would be and how and why their solution would lead to the desired result. In this work, we analyze answers to the first question and provide a methodology for the second. We systematically derive a joint power rate control strategy for VSC which optimizes reception performance for a targeted sender-receiver distance. We start by laying out why we consider average (or percentile of) packet Inter-Reception Time (IRT) at the targeted awareness distance to be a suitable metric for our purpose. Then, we analyze a wide range of Tx parameters to identify which combinations optimize reception in a homogeneous scenario. We show that for each sender-receiver distance, there is an optimal Tx power which, unlike the corresponding Tx rate, is independent of node density. In addition, we analyze the Pareto optimal Tx parameter combinations for two groups of vehicles with different target distances adapting at the same time. We show that the majority of these combinations use the same Tx power as identified in the homogeneous case. We conclude that a simple and efficient strategy to optimize reception performance is to select Tx power w.r.t. the targeted distance and to adapt Tx rate w.r.t. channel load. Vehicle Safety Communications (VSC) is advancing rapidly towards product development and field testing. While a number of possible solutions have been proposed, the question remains open as how such a system will address the issue of scalability in its actual deployment. This paper presents a design methodology for congestion control in VSC as well as the description and evaluation of a resulting rate adaption oriented protocol named PULSAR. We start with a list of design principles reflecting the state of the art that define why and how vehicles should behave while responding to channel congestion in order to ensure fairness and support the needs of safety applications. From these principles, we derive protocol building blocks required to fulfill the defined objectives. Then, the actual protocol is described and assessed in detail, including a discussion on the intricate features of channel load assessment, rate adaptation and information sharing. A comparison with other state-of-the-art protocols shows that “details matter” with respect to the temporal and spatial dimensions of the protocol outcome. We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices ( spl lambda sub ij ) that the system can stably support - where ( spl lambda sub ij ) represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed which stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an ad-hoc wireless network where channel variations are due to user mobility, and compare its performance with the Grossglauser-Tse (2001) relay model. We consider dynamic routing and power allocation for a wireless network with time-varying channels. The network consists of power constrained nodes that transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices ( spl lambda sub ij ) that the system can stably support-where spl lambda sub ij represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed that stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an ad hoc wireless network, where channel variations are due to user mobility. Centralized and decentralized implementations are compared, and the stability region of the decentralized algorithm is shown to contain that of the mobile relay strategy developed by Grossglauser and Tse (2002). When terminals powered by a finite battery source are used for wireless communications, energy constraints are likely to influence the choice of error control protocols. Therefore, we propose the average number of correctly transmitted packets during the lifetime of the battery as a new metric. In particular, we study the go-back-N retransmission protocol operating over a wireless channel using a finite energy source with a flat power profile. We characterize the sensitivity of the total number of correctly transmitted packets to the choice of the output power level. We then generalize our results to arbitrary power profiles through both a recursive technique and Markov analysis. Finally, we compare the performance of go-back-N with an adaptive error control protocol that slows down the transmission rate when the channel is impaired, and document the advantages. The MAC protocol of a cognitive radio (CR) device should allow it to access unused or under-utilized spectrum without (or with minimal) interference to primary users dynamically. To fulfill such a goal, we propose a cognitive MAC protocol using statistical channel allocation and call it SCA-MAC in this work. SCA-MAC is a CSMA CA-based protocol, which exploits statistics of spectrum usage for decision making on channel access. For each transmission, the sender negotiates with the receiver on transmission parameters through the control channel. A model is developed for CR devices to evaluate the successful rate of transmission. A CR device should pass the threshold of the successful transmission rate via negotiation before it can begin a valid transmission on data channels. The operating range and channel aggregation are two control parameters introduced to maintain the MAC performance. To validate our ideas, we conducted theoretical analysis and simulations to show that SCA-MAC does improve the throughput performance and guarantee the interference to incumbents to be bounded by a predetermined acceptable rate. The proposed MAC protocol does not need a centralized controller, as the negotiation between the sender and the receiver is performed using the CSMA CA-based algorithm. In this paper, we revisit the problem of determining the minimum-length schedule that satisfies certain traffic demands in a wireless network. Traditional approaches for the determination of minimum-length schedules are based on a collision channel model, in which neighboring transmissions cause destructive interference if and only if they are within the "interference region" of the receiving nodes. By contrast, we adopt here a more realistic model for the physical layer by requiring that a threshold be exceeded by the signal-to-interference-plus-noise ratio (SINR) for a transmission to be successful. We present a novel formulation of the problem that incorporates various power and rate adaptation schemes while seamlessly integrating the generation of "matchings" (i.e., sets of links that can be activated simultaneously) by taking into consideration the SINR constraints at the receivers. For the formulated problem, we propose a column-generation-based solution method and show that it theoretically converges to a globally optimal solution, with a potential advantage of not having to enumerate all the feasible matchings a priori. We also discuss the influence of power control, spatial reuse, and variable transmission rates on network performance. Furthermore, we include aspects of the routing problem and provide computational results for our proposed column-generation-based solution procedure. In this paper we consider an IEEE 802.15.4-based Wireless Body Area Network, where wearable sensor devices are distributed on a body and have to send the measured data to a coordinator. The Carrier Sense Multiple Access with Collision Avoidance algorithm defined by the standard is used as Medium Access Control protocol, whereas different modulation schemes are assumed to be available at the physical layer. We propose a novel Link Adaptation (LA) strategy, where nodes select the modulation scheme according to the experienced channel quality and level of interference. The novelty lays in the fact that in case of large Signal-to-Noise Ratio and low Signal-to-Interference Ratio nodes increase the bit rate, instead of reducing it, as largely done in the works present in the literature. The reduction of the bit rate, in fact, allows to decrease the time the channel is occupied and, therefore, the collision probability. Performance is evaluated in terms of packet error rate and results achieved with and without LA are compared. Results show that the proposed strategy improves performance. In this paper, we investigate distributed control of multiple secondary users attempting to access the channel of a high priority primary user. Our aim is to maximize the sum cognitive (secondary) user throughput under the constraint of primary user's queue stability. We consider the effect of primary user link adaptation that allows the primary transmitter (PTx) to adapt its transmission rate in response to the secondary interference-level at the primary receiver (PRx). To control the sum secondary interference to PRx beyond the traditional collision-avoidance paradigm, we propose a novel power-control algorithm for secondary nodes to function. To develop such a distributed algorithm and to improve secondary user adaptability, we allow secondary nodes to monitor primary's radio link control information on the feedback channel. We present practical schemes that approximate the optimum solution without relying on global channel information at each secondary node. We consider QoS-aware spectrum sharing in cognitive wireless networks where secondary users are allowed to access the spectrum owned by a primary network provider. The interference from secondary users to primary users is constrained to be below the tolerable limit. Also, signal to interference plus noise ratio (SINR) of each secondary user is maintained higher than a desired level for QoS insurance. When network load is high, admission control needs to be performed to satisfy both QoS and interference constraints. We propose an admission control algorithm which is performed jointly with power control such that QoS requirements of all admitted secondary users are satisfied while keeping the interference to primary users below the tolerable limit. When all secondary users can be supported at minimum rates, we allow them to increase their transmission rates and share the spectrum in a fair manner. We formulate the joint power rate allocation with max-min fairness criterion as an optimization problem. We show how to transform it into a convex optimization problem so that its globally optimal solution can be obtained. Numerical results show that the proposed admission control algorithm achieves performance very close to the optimal solution. Also, impacts of different system and QoS parameters on the network performance are investigated for both admission control and rate power allocation problems. Direct radio-based vehicle-to-vehicle communication can help prevent accidents by providing accurate and up-to-date local status and hazard information to the driver. In this paper, we assume that two types of messages are used for traffic safety-related communication: 1) Periodic messages (ldquobeaconsrdquo) that are sent by all vehicles to inform their neighbors about their current status (i.e., position) and 2) event-driven messages that are sent whenever a hazard has been detected. In IEEE 802.11 distributed-coordination-function-based vehicular networks, interferences and packet collisions can lead to the failure of the reception of safety-critical information, in particular when the beaconing load leads to an almost-saturated channel, as it could easily happen in many critical vehicular traffic conditions. In this paper, we demonstrate the importance of transmit power control to avoid saturated channel conditions and ensure the best use of the channel for safety-related purposes. We propose a distributed transmit power control method based on a strict fairness criterion, i.e., distributed fair power adjustment for vehicular environments (D-FPAV), to control the load of periodic messages on the channel. The benefits are twofold: 1) The bandwidth is made available for higher priority data like dissemination of warnings, and 2) beacons from different vehicles are treated with ldquoequal rights,rdquo and therefore, the best possible reception under the available bandwidth constraints is ensured. We formally prove the fairness of the proposed approach. Then, we make use of the ns-2 simulator that was significantly enhanced by realistic highway mobility patterns, improved radio propagation, receiver models, and the IEEE 802.11p specifications to show the beneficial impact of D-FPAV for safety-related communications. We finally put forward a method, i.e., emergency message dissemination for vehicular environments (EMDV), for fast and effective multihop information dissemination of event-driven messages and show that EMDV benefits of the beaconing load control provided by D-FPAV with respect to both probability of reception and latency. In mobile packet data and voice networks, a special coding scheme, known as the incremental redundancy hybrid ARQ (IR HARQ), achieves higher throughput efficiency than ordinary turbo codes by adapting its error correcting code redundancy to fluctuating channel conditions characteristic for this application. An IR HARQ protocol operates as follows. Initially, the information bits are encoded by a “mother” code and a selected number of parity bits are transmitted. If a retransmission is requested, only additional selected parity bits are transmitted. At the receiving end, the additional parity bits are combined with the previously received bits, allowing for an increase in the error correction capacity. This procedure is repeated after each subsequent retransmission request until the entire codeword of the mother code is transmitted. A number of important issues such as error rate performance after each transmission on time varying channels, and rate and power control are difficult to analyze in a network employing a particular HARQ scheme, i.e., a given mother code and given selection of bits for each transmission. By relaxing only the latter constraint, namely, by allowing random selection of the bits for each transmission, we provide very good estimates of error rates allowing us to address to a certain extent the rate and power control problem. The importance of spatial reuse in wireless ad hoc networks has been long recognized as a key to improving the network capacity. In this paper, we show that 1) in the case that the achievable channel rate follows the Shannon capacity, spatial reuse depends only on the ratio of the transmit power to the carrier sense threshold and 2) in the case that only a set of discrete data rates are available, as a control knob for sustaining achievable data rates, tuning the transmit power provides more sophisticated rate control over tuning the carrier sense threshold, provided that there is a sufficient number of power levels available. Based on the findings, we then propose a decentralized power and rate control algorithm to enable each node to adjust, based on its signal interference level, its transmit power and data rate. The transmit power is so determined that the transmitter can sustain a high data rate while keeping the adverse interference effect on the other neighboring concurrent transmissions minimal. Simulation results have shown that compared to existing carrier sense threshold tuning algorithms, the proposed power and rate control algorithm yields higher network capacity.