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In this paper, we propose a new secret sharing scheme for secure multi-party computation. We present a general framework that allows us to construct efficient secret sharing schemes from channel coding techniques for the wiretap channel. The resulting schemes can be employed to securely calculate linear functions of data that are distributed in a network without leaking any information on the data except the desired result. For the examples considered in this paper, our schemes minimize the communication overhead while keeping the data perfectly secure. Compared to conventional schemes, for which the communication overhead grows quadratically in the number of clients in the considered scenarios, the communication overhead for our approach grows only linearly with the number of clients. This property is maintained even if our secret sharing scheme is set up to introduce redundancy in order to compensate for losses of secret shares. While we only consider the case of passive eavesdroppers and implementations based on nested Reed-Solomon codes in this paper, the proposed framework can also be applied in other cases (e.g., when clients tamper with the data) by taking into account the effects of attacks in the design of the underlying wiretap code., QC 20150521

In this paper, we propose a new secret sharing scheme for secure multi-party computation. We present a general framework that allows us to construct efficient secret sharing schemes from channel coding techniques for the wiretap channel. The resulting schemes can be employed to securely calculate linear functions of data that are distributed in a network without leaking any information on the data except the desired result. For the examples considered in this paper, our schemes minimize the communication overhead while keeping the data perfectly secure. Compared to conventional schemes, for which the communication overhead grows quadratically in the number of clients in the considered scenarios, the communication overhead for our approach grows only linearly with the number of clients. This property is maintained even if our secret sharing scheme is set up to introduce redundancy in order to compensate for losses of secret shares. While we only consider the case of passive eavesdroppers and implementations based on nested Reed-Solomon codes in this paper, the proposed framework can also be applied in other cases (e.g., when clients tamper with the data) by taking into account the effects of attacks in the design of the underlying wiretap code., QC 20150521

In this paper, we propose a new secret sharing scheme for secure multi-party computation. We present a general framework that allows us to construct efficient secret sharing schemes from channel coding techniques for the wiretap channel. The resulting schemes can be employed to securely calculate linear functions of data that are distributed in a network without leaking any information on the data except the desired result. For the examples considered in this paper, our schemes minimize the communication overhead while keeping the data perfectly secure. Compared to conventional schemes, for which the communication overhead grows quadratically in the number of clients in the considered scenarios, the communication overhead for our approach grows only linearly with the number of clients. This property is maintained even if our secret sharing scheme is set up to introduce redundancy in order to compensate for losses of secret shares. While we only consider the case of passive eavesdroppers and implementations based on nested Reed-Solomon codes in this paper, the proposed framework can also be applied in other cases (e.g., when clients tamper with the data) by taking into account the effects of attacks in the design of the underlying wiretap code., QC 20150521

In this paper, we propose a new secret sharing scheme for secure multi-party computation. We present a general framework that allows us to construct efficient secret sharing schemes from channel coding techniques for the wiretap channel. The resulting schemes can be employed to securely calculate linear functions of data that are distributed in a network without leaking any information on the data except the desired result. For the examples considered in this paper, our schemes minimize the communication overhead while keeping the data perfectly secure. Compared to conventional schemes, for which the communication overhead grows quadratically in the number of clients in the considered scenarios, the communication overhead for our approach grows only linearly with the number of clients. This property is maintained even if our secret sharing scheme is set up to introduce redundancy in order to compensate for losses of secret shares. While we only consider the case of passive eavesdroppers and implementations based on nested Reed-Solomon codes in this paper, the proposed framework can also be applied in other cases (e.g., when clients tamper with the data) by taking into account the effects of attacks in the design of the underlying wiretap code., QC 20150521

In this paper, we propose a new secret sharing scheme for secure multi-party computation. We present a general framework that allows us to construct efficient secret sharing schemes from channel coding techniques for the wiretap channel. The resulting schemes can be employed to securely calculate linear functions of data that are distributed in a network without leaking any information on the data except the desired result. For the examples considered in this paper, our schemes minimize the communication overhead while keeping the data perfectly secure. Compared to conventional schemes, for which the communication overhead grows quadratically in the number of clients in the considered scenarios, the communication overhead for our approach grows only linearly with the number of clients. This property is maintained even if our secret sharing scheme is set up to introduce redundancy in order to compensate for losses of secret shares. While we only consider the case of passive eavesdroppers and implementations based on nested Reed-Solomon codes in this paper, the proposed framework can also be applied in other cases (e.g., when clients tamper with the data) by taking into account the effects of attacks in the design of the underlying wiretap code., QC 20150521

In Wireless Sensor Networks (WSNs), to supply energy to the sensor nodes, wireless energy transfer (WET) is a promising technique. One of the most efficient procedures to transfer energy to the sensor nodes consists in using a sharp wireless energy beam from the base station to each node at a time. A natural fundamental question is what is the lifetime ensured by WET and how to maximize the network lifetime by scheduling the transmissions of the energy beams. In this paper, such a question is addressed by posing a new lifetime maximization problem for WET enabled WSNs. The binary nature of the energy transmission process introduces a binary constraint in the optimization problem, which makes challenging the investigation of the fundamental properties of WET and the computation of the optimal solution. The sufficient condition for which the WET makes WSNs immortal is established as function of the WET parameters. When such a condition is not met, a solution algorithm to the maximum lifetime problem is proposed. The numerical results show that the lifetime achieved by the proposed algorithm increases by about 50% compared to the case without WET, for a WSN with a small to medium size number of nodes. This suggests that it is desirable to schedule WET to prolong lifetime of WSNs having small or medium network sizes., QC 20170131

In this paper, we consider a discrete time linear quadratic Gaussian (LQG) control problem in which state information of the plant is encoded in a variable-length binary codeword at every time step, and a control input is determined based on the codewords generated in the past. We derive a lower bound of the rate achievable by the class of prefix-free codes attaining the required LQG control performance. This lower bound coincides with the infimum of a certain directed information expression, and is computable by semidefinite programming (SDP). Based on a technique by Silva et al., we also provide an upper bound of the best achievable rate by constructing a controller equipped with a uniform quantizer with subtractive dither and Shannon-Fano coding. The gap between the obtained lower and upper bounds is less than 0:754r + 1 bits per time step regardless of the required LQG control performance, where r is the rank of a signal-to-noise ratio matrix obtained by SDP, which is no greater than the dimension of the state., QC 20161122

In Wireless Sensor Networks (WSNs), to supply energy to the sensor nodes, wireless energy transfer (WET) is a promising technique. One of the most efficient procedures to transfer energy to the sensor nodes consists in using a sharp wireless energy beam from the base station to each node at a time. A natural fundamental question is what is the lifetime ensured by WET and how to maximize the network lifetime by scheduling the transmissions of the energy beams. In this paper, such a question is addressed by posing a new lifetime maximization problem for WET enabled WSNs. The binary nature of the energy transmission process introduces a binary constraint in the optimization problem, which makes challenging the investigation of the fundamental properties of WET and the computation of the optimal solution. The sufficient condition for which the WET makes WSNs immortal is established as function of the WET parameters. When such a condition is not met, a solution algorithm to the maximum lifetime problem is proposed. The numerical results show that the lifetime achieved by the proposed algorithm increases by about 50% compared to the case without WET, for a WSN with a small to medium size number of nodes. This suggests that it is desirable to schedule WET to prolong lifetime of WSNs having small or medium network sizes., QC 20170131

In Wireless Sensor Networks (WSNs), to supply energy to the sensor nodes, wireless energy transfer (WET) is a promising technique. One of the most efficient procedures to transfer energy to the sensor nodes consists in using a sharp wireless energy beam from the base station to each node at a time. A natural fundamental question is what is the lifetime ensured by WET and how to maximize the network lifetime by scheduling the transmissions of the energy beams. In this paper, such a question is addressed by posing a new lifetime maximization problem for WET enabled WSNs. The binary nature of the energy transmission process introduces a binary constraint in the optimization problem, which makes challenging the investigation of the fundamental properties of WET and the computation of the optimal solution. The sufficient condition for which the WET makes WSNs immortal is established as function of the WET parameters. When such a condition is not met, a solution algorithm to the maximum lifetime problem is proposed. The numerical results show that the lifetime achieved by the proposed algorithm increases by about 50% compared to the case without WET, for a WSN with a small to medium size number of nodes. This suggests that it is desirable to schedule WET to prolong lifetime of WSNs having small or medium network sizes., QC 20170131

In Wireless Sensor Networks (WSNs), to supply energy to the sensor nodes, wireless energy transfer (WET) is a promising technique. One of the most efficient procedures to transfer energy to the sensor nodes consists in using a sharp wireless energy beam from the base station to each node at a time. A natural fundamental question is what is the lifetime ensured by WET and how to maximize the network lifetime by scheduling the transmissions of the energy beams. In this paper, such a question is addressed by posing a new lifetime maximization problem for WET enabled WSNs. The binary nature of the energy transmission process introduces a binary constraint in the optimization problem, which makes challenging the investigation of the fundamental properties of WET and the computation of the optimal solution. The sufficient condition for which the WET makes WSNs immortal is established as function of the WET parameters. When such a condition is not met, a solution algorithm to the maximum lifetime problem is proposed. The numerical results show that the lifetime achieved by the proposed algorithm increases by about 50% compared to the case without WET, for a WSN with a small to medium size number of nodes. This suggests that it is desirable to schedule WET to prolong lifetime of WSNs having small or medium network sizes., QC 20170131

In Wireless Sensor Networks (WSNs), to supply energy to the sensor nodes, wireless energy transfer (WET) is a promising technique. One of the most efficient procedures to transfer energy to the sensor nodes consists in using a sharp wireless energy beam from the base station to each node at a time. A natural fundamental question is what is the lifetime ensured by WET and how to maximize the network lifetime by scheduling the transmissions of the energy beams. In this paper, such a question is addressed by posing a new lifetime maximization problem for WET enabled WSNs. The binary nature of the energy transmission process introduces a binary constraint in the optimization problem, which makes challenging the investigation of the fundamental properties of WET and the computation of the optimal solution. The sufficient condition for which the WET makes WSNs immortal is established as function of the WET parameters. When such a condition is not met, a solution algorithm to the maximum lifetime problem is proposed. The numerical results show that the lifetime achieved by the proposed algorithm increases by about 50% compared to the case without WET, for a WSN with a small to medium size number of nodes. This suggests that it is desirable to schedule WET to prolong lifetime of WSNs having small or medium network sizes., QC 20170131

This paper proposes a set of piecewise Toeplitz matrices as the linear mapping/sensing operator A: Rn1×n2 → RM for recovering low rank matrices from few measurements. We prove that such operators efficiently encode the information so there exists a unique reconstruction matrix under mild assumptions. This work provides a significant extension of the compressed sensing and rank minimization theory, and it achieves a tradeoff between reducing the memory required for storing the sampling operator from O(n1n2M) to O(max(n1, n2)M) but at the expense of increasing the number of measurements by r. Simulation results show that the proposed operator can recover low rank matrices efficiently with a reconstruction performance close to the cases of using random unstructured operators., QC 20150605

In this paper, we propose a new algorithm for recovery of low-rank matrices from compressed linear measurements. The underlying idea of this algorithm is to closely approximate the rank function with a smooth function of singular values, and then minimize the resulting approximation subject to the linear constraints. The accuracy of the approximation is controlled via a scaling parameter δ, where a smaller δ corresponds to a more accurate fitting. The consequent optimization problem for any finite δ is nonconvex. Therefore, to decrease the risk of ending up in local minima, a series of optimizations is performed, starting with optimizing a rough approximation (a large δ) and followed by successively optimizing finer approximations of the rank with smaller δ's. To solve the optimization problem for any δ > 0, it is converted to a new program in which the cost is a function of two auxiliary positive semidefinite variables. The paper shows that this new program is concave and applies a majorize-minimize technique to solve it which, in turn, leads to a few convex optimization iterations. This optimization scheme is also equivalent to a reweighted Nuclear Norm Minimization (NNM). For any δ > 0, we derive a necessary and sufficient condition for the exact recovery which are weaker than those corresponding to NNM. On the numerical side, the proposed algorithm is compared to NNM and a reweighted NNM in solving affine rank minimization and matrix completion problems showing its considerable and consistent superiority in terms of success rate., QC 20150417

In this paper, we propose a new algorithm for recovery of low-rank matrices from compressed linear measurements. The underlying idea of this algorithm is to closely approximate the rank function with a smooth function of singular values, and then minimize the resulting approximation subject to the linear constraints. The accuracy of the approximation is controlled via a scaling parameter δ, where a smaller δ corresponds to a more accurate fitting. The consequent optimization problem for any finite δ is nonconvex. Therefore, to decrease the risk of ending up in local minima, a series of optimizations is performed, starting with optimizing a rough approximation (a large δ) and followed by successively optimizing finer approximations of the rank with smaller δ's. To solve the optimization problem for any δ > 0, it is converted to a new program in which the cost is a function of two auxiliary positive semidefinite variables. The paper shows that this new program is concave and applies a majorize-minimize technique to solve it which, in turn, leads to a few convex optimization iterations. This optimization scheme is also equivalent to a reweighted Nuclear Norm Minimization (NNM). For any δ > 0, we derive a necessary and sufficient condition for the exact recovery which are weaker than those corresponding to NNM. On the numerical side, the proposed algorithm is compared to NNM and a reweighted NNM in solving affine rank minimization and matrix completion problems showing its considerable and consistent superiority in terms of success rate., QC 20150417

In this paper, we propose a new algorithm for recovery of low-rank matrices from compressed linear measurements. The underlying idea of this algorithm is to closely approximate the rank function with a smooth function of singular values, and then minimize the resulting approximation subject to the linear constraints. The accuracy of the approximation is controlled via a scaling parameter δ, where a smaller δ corresponds to a more accurate fitting. The consequent optimization problem for any finite δ is nonconvex. Therefore, to decrease the risk of ending up in local minima, a series of optimizations is performed, starting with optimizing a rough approximation (a large δ) and followed by successively optimizing finer approximations of the rank with smaller δ's. To solve the optimization problem for any δ > 0, it is converted to a new program in which the cost is a function of two auxiliary positive semidefinite variables. The paper shows that this new program is concave and applies a majorize-minimize technique to solve it which, in turn, leads to a few convex optimization iterations. This optimization scheme is also equivalent to a reweighted Nuclear Norm Minimization (NNM). For any δ > 0, we derive a necessary and sufficient condition for the exact recovery which are weaker than those corresponding to NNM. On the numerical side, the proposed algorithm is compared to NNM and a reweighted NNM in solving affine rank minimization and matrix completion problems showing its considerable and consistent superiority in terms of success rate., QC 20150417

In this paper, we propose a new algorithm for recovery of low-rank matrices from compressed linear measurements. The underlying idea of this algorithm is to closely approximate the rank function with a smooth function of singular values, and then minimize the resulting approximation subject to the linear constraints. The accuracy of the approximation is controlled via a scaling parameter δ, where a smaller δ corresponds to a more accurate fitting. The consequent optimization problem for any finite δ is nonconvex. Therefore, to decrease the risk of ending up in local minima, a series of optimizations is performed, starting with optimizing a rough approximation (a large δ) and followed by successively optimizing finer approximations of the rank with smaller δ's. To solve the optimization problem for any δ > 0, it is converted to a new program in which the cost is a function of two auxiliary positive semidefinite variables. The paper shows that this new program is concave and applies a majorize-minimize technique to solve it which, in turn, leads to a few convex optimization iterations. This optimization scheme is also equivalent to a reweighted Nuclear Norm Minimization (NNM). For any δ > 0, we derive a necessary and sufficient condition for the exact recovery which are weaker than those corresponding to NNM. On the numerical side, the proposed algorithm is compared to NNM and a reweighted NNM in solving affine rank minimization and matrix completion problems showing its considerable and consistent superiority in terms of success rate., QC 20150417

This paper considers a multi-input multi-output(MIMO) interference network in which each transmitter intendsto communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied to align theinterference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference canhence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link dependson the transmission power of the unintended transmitters. Tosolve this problem, we propose an iterative algorithm to performstochastic power control and transceiver design based on onlynoisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs., QC 20130820, RAMCOORAN

This paper considers a multi-input multi-output(MIMO) interference network in which each transmitter intendsto communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied to align theinterference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference canhence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link dependson the transmission power of the unintended transmitters. Tosolve this problem, we propose an iterative algorithm to performstochastic power control and transceiver design based on onlynoisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs., QC 20130820, RAMCOORAN

This paper considers a multi-input multi-output(MIMO) interference network in which each transmitter intendsto communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied to align theinterference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference canhence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link dependson the transmission power of the unintended transmitters. Tosolve this problem, we propose an iterative algorithm to performstochastic power control and transceiver design based on onlynoisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs., QC 20130820, RAMCOORAN

This paper considers a multi-input multi-output(MIMO) interference network in which each transmitter intendsto communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied to align theinterference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference canhence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link dependson the transmission power of the unintended transmitters. Tosolve this problem, we propose an iterative algorithm to performstochastic power control and transceiver design based on onlynoisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs., QC 20130820, RAMCOORAN

This paper considers a multi-input multi-output(MIMO) interference network in which each transmitter intendsto communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied to align theinterference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference canhence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link dependson the transmission power of the unintended transmitters. Tosolve this problem, we propose an iterative algorithm to performstochastic power control and transceiver design based on onlynoisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs., QC 20130820, RAMCOORAN

The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Sodertalje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios., © 2012 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.QC20120927

The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Sodertalje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios., © 2012 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.QC20120927

The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Sodertalje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios., © 2012 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.QC20120927

The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Sodertalje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios., © 2012 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.QC20120927

The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Sodertalje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios., © 2012 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.QC20120927

In 1968, Witsenhausen introduced his famous counterexample where he showed that even in the simple linear quadratic static team decision problem, complex nonlinear decisions could outperform any given linear decision. This problem has served as a benchmark problem for decades where researchers try to achieve the optimal solution. This paper introduces a systematic iterative source-channel coding approach to solve problems of the Witsenhausen Counterexample-character. The advantage of the presented approach is its simplicity. Also, no assumptions are made about the shape of the space of policies. The minimal cost obtatined using the introduced method is 0.16692462, which is the lowest known thus far., © 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 20111212

In 1968, Witsenhausen introduced his famous counterexample where he showed that even in the simple linear quadratic static team decision problem, complex nonlinear decisions could outperform any given linear decision. This problem has served as a benchmark problem for decades where researchers try to achieve the optimal solution. This paper introduces a systematic iterative source-channel coding approach to solve problems of the Witsenhausen Counterexample-character. The advantage of the presented approach is its simplicity. Also, no assumptions are made about the shape of the space of policies. The minimal cost obtatined using the introduced method is 0.16692462, which is the lowest known thus far., © 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 20111212

In 1968, Witsenhausen introduced his famous counterexample where he showed that even in the simple linear quadratic static team decision problem, complex nonlinear decisions could outperform any given linear decision. This problem has served as a benchmark problem for decades where researchers try to achieve the optimal solution. This paper introduces a systematic iterative source-channel coding approach to solve problems of the Witsenhausen Counterexample-character. The advantage of the presented approach is its simplicity. Also, no assumptions are made about the shape of the space of policies. The minimal cost obtatined using the introduced method is 0.16692462, which is the lowest known thus far., © 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 20111212

In 1968, Witsenhausen introduced his famous counterexample where he showed that even in the simple linear quadratic static team decision problem, complex nonlinear decisions could outperform any given linear decision. This problem has served as a benchmark problem for decades where researchers try to achieve the optimal solution. This paper introduces a systematic iterative source-channel coding approach to solve problems of the Witsenhausen Counterexample-character. The advantage of the presented approach is its simplicity. Also, no assumptions are made about the shape of the space of policies. The minimal cost obtatined using the introduced method is 0.16692462, which is the lowest known thus far., © 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 20111212

In 1968, Witsenhausen introduced his famous counterexample where he showed that even in the simple linear quadratic static team decision problem, complex nonlinear decisions could outperform any given linear decision. This problem has served as a benchmark problem for decades where researchers try to achieve the optimal solution. This paper introduces a systematic iterative source-channel coding approach to solve problems of the Witsenhausen Counterexample-character. The advantage of the presented approach is its simplicity. Also, no assumptions are made about the shape of the space of policies. The minimal cost obtatined using the introduced method is 0.16692462, which is the lowest known thus far., © 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 20111212

The simulation models of wireless networks rapidly increase in complexity to accurately model wireless channel characteristics and the properties of advanced transmission technologies. Such detailed models typically lead to a high computational load per simulation event that accumulates to extensive simulation runtimes. Reducing runtimes through parallelization is challenging since it depends on detecting causally independent events that can execute concurrently. Most existing approaches base this detection on lookaheads derived from channel propagation latency or protocol characteristics. In wireless networks, these lookaheads are typically short, causing the potential for parallelization and the achievable speedup to remain small. This paper presents Horizon, which unlocks a substantial portion of a simulation model's workload for parallelization by going beyond the traditional lookahead. We show how to augment discrete events with durations to identify a much larger horizon of independent simulation events and efficiently schedule them on multi-core systems. Our evaluation shows that this approach can significantly cut down the runtime of simulations, in particular for complex and accurate models of wireless networks., QC 20111116

The simulation models of wireless networks rapidly increase in complexity to accurately model wireless channel characteristics and the properties of advanced transmission technologies. Such detailed models typically lead to a high computational load per simulation event that accumulates to extensive simulation runtimes. Reducing runtimes through parallelization is challenging since it depends on detecting causally independent events that can execute concurrently. Most existing approaches base this detection on lookaheads derived from channel propagation latency or protocol characteristics. In wireless networks, these lookaheads are typically short, causing the potential for parallelization and the achievable speedup to remain small. This paper presents Horizon, which unlocks a substantial portion of a simulation model's workload for parallelization by going beyond the traditional lookahead. We show how to augment discrete events with durations to identify a much larger horizon of independent simulation events and efficiently schedule them on multi-core systems. Our evaluation shows that this approach can significantly cut down the runtime of simulations, in particular for complex and accurate models of wireless networks., QC 20111116

The simulation models of wireless networks rapidly increase in complexity to accurately model wireless channel characteristics and the properties of advanced transmission technologies. Such detailed models typically lead to a high computational load per simulation event that accumulates to extensive simulation runtimes. Reducing runtimes through parallelization is challenging since it depends on detecting causally independent events that can execute concurrently. Most existing approaches base this detection on lookaheads derived from channel propagation latency or protocol characteristics. In wireless networks, these lookaheads are typically short, causing the potential for parallelization and the achievable speedup to remain small. This paper presents Horizon, which unlocks a substantial portion of a simulation model's workload for parallelization by going beyond the traditional lookahead. We show how to augment discrete events with durations to identify a much larger horizon of independent simulation events and efficiently schedule them on multi-core systems. Our evaluation shows that this approach can significantly cut down the runtime of simulations, in particular for complex and accurate models of wireless networks., QC 20111116

The simulation models of wireless networks rapidly increase in complexity to accurately model wireless channel characteristics and the properties of advanced transmission technologies. Such detailed models typically lead to a high computational load per simulation event that accumulates to extensive simulation runtimes. Reducing runtimes through parallelization is challenging since it depends on detecting causally independent events that can execute concurrently. Most existing approaches base this detection on lookaheads derived from channel propagation latency or protocol characteristics. In wireless networks, these lookaheads are typically short, causing the potential for parallelization and the achievable speedup to remain small. This paper presents Horizon, which unlocks a substantial portion of a simulation model's workload for parallelization by going beyond the traditional lookahead. We show how to augment discrete events with durations to identify a much larger horizon of independent simulation events and efficiently schedule them on multi-core systems. Our evaluation shows that this approach can significantly cut down the runtime of simulations, in particular for complex and accurate models of wireless networks., QC 20111116

The simulation models of wireless networks rapidly increase in complexity to accurately model wireless channel characteristics and the properties of advanced transmission technologies. Such detailed models typically lead to a high computational load per simulation event that accumulates to extensive simulation runtimes. Reducing runtimes through parallelization is challenging since it depends on detecting causally independent events that can execute concurrently. Most existing approaches base this detection on lookaheads derived from channel propagation latency or protocol characteristics. In wireless networks, these lookaheads are typically short, causing the potential for parallelization and the achievable speedup to remain small. This paper presents Horizon, which unlocks a substantial portion of a simulation model's workload for parallelization by going beyond the traditional lookahead. We show how to augment discrete events with durations to identify a much larger horizon of independent simulation events and efficiently schedule them on multi-core systems. Our evaluation shows that this approach can significantly cut down the runtime of simulations, in particular for complex and accurate models of wireless networks., QC 20111116

To achieve satisfactory overall performance, optimal rate allocation in a networked control system with highly limited communication resources is instrumental. In this paper, a rate allocation technique for state feedback control in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall cost is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved. It is shown that a non-uniform quantization is in general the best strategy for state feedback control over noisy channels. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110124

Optimal rate allocation in a networked control system with limited communication resources is instrumental to achieve satisfactory overall performance. In this paper, a practical rate allocation technique for state estimation in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall distortion is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved by using Lagrange duality. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110113

Optimal rate allocation in a networked control system with highly limited communication resources is instrumental to achieve satisfactory overall performance. In this paper, we propose a rate allocation technique for state feedback control in linear dynamic systems over a noisy channel. Our method consists of two steps: (i) the overall distortion is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved. We show that a non-uniform quantization is in general the best strategy for state feedback control over noisy channels. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance compared to arbitrarily selected rate allocations., QC 20120215

To achieve satisfactory overall performance, optimal rate allocation in a networked control system with highly limited communication resources is instrumental. In this paper, a rate allocation technique for state feedback control in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall cost is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved. It is shown that a non-uniform quantization is in general the best strategy for state feedback control over noisy channels. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110124

This paper proposes Utility Based Adaptive Frequency Hopping (UBAFH), an adaptive hopping technique implementing a new paradigm for frequency hopping systems. Traditional adaptive algorithms aim at identifying bad channels that are consequently removed from the hopset. UBAFH instead utilizes all the available frequencies but assigns different usage probabilities to different channels according to the experienced channel conditions. Opportune upper and lower limits are used in order to bound these usage probabilities and achieve a desired level of frequency diversity. We simulate the behavior of UBAFH over frequency selective fading channels and compare the achieved packet error rate and throughput with the ones of IEEE 802.15.1 and with the adaptive frequency hopping implementation proposed by IEEE 802.15.2 showing that UBAFH outperforms both approaches., QC 20130506

Optimal rate allocation in a networked control system with limited communication resources is instrumental to achieve satisfactory overall performance. In this paper, a practical rate allocation technique for state estimation in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall distortion is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved by using Lagrange duality. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110113

To achieve satisfactory overall performance, optimal rate allocation in a networked control system with highly limited communication resources is instrumental. In this paper, a rate allocation technique for state feedback control in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall cost is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved. It is shown that a non-uniform quantization is in general the best strategy for state feedback control over noisy channels. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110124

To achieve satisfactory overall performance, optimal rate allocation in a networked control system with highly limited communication resources is instrumental. In this paper, a rate allocation technique for state feedback control in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall cost is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved. It is shown that a non-uniform quantization is in general the best strategy for state feedback control over noisy channels. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110124

Optimal rate allocation in a networked control system with limited communication resources is instrumental to achieve satisfactory overall performance. In this paper, a practical rate allocation technique for state estimation in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall distortion is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved by using Lagrange duality. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110113

Optimal rate allocation in a networked control system with limited communication resources is instrumental to achieve satisfactory overall performance. In this paper, a practical rate allocation technique for state estimation in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall distortion is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved by using Lagrange duality. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110113

Optimal rate allocation in a networked control system with limited communication resources is instrumental to achieve satisfactory overall performance. In this paper, a practical rate allocation technique for state estimation in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall distortion is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved by using Lagrange duality. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110113

To achieve satisfactory overall performance, optimal rate allocation in a networked control system with highly limited communication resources is instrumental. In this paper, a rate allocation technique for state feedback control in linear dynamic systems over a noisy channel is proposed. The method consists of two steps: (i) the overall cost is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize the overall distortion is solved. It is shown that a non-uniform quantization is in general the best strategy for state feedback control over noisy channels. Monte Carlo simulations illustrate the proposed scheme, which is shown to have good performance when compared to arbitrarily selected rate allocations., QC 20110124

Bandwidth limitations and energy constraints set severe restrictions on the design of control systems that utilize wireless sensor and actuator networks. It is common in these systems that a sensor node needs not be continuously monitored, but communicates to the controller only at certain instances when it detects a disturbance event. In this paper, such a scenario is studied and particular emphasis is on efficient utilization of the shared communication resources. Encoder-decoder design for an event-based control system with the plant affected by pulse disturbances is considered. A new iterative procedure is proposed which can jointly optimize encoder-decoder pairs for a certainty equivalent controller. The goal is to minimize a design criterion, in particular, a linear quadratic cost over a finite horizon. The algorithm leads to a feasible design of time-varying non-uniform encoder-decoder pairs. Numerical results demonstrate significant improvements in performance compared to a system using uniform quantization., © 2006 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 20101221

Bandwidth limitations and energy constraints set severe restrictions on the design of control systems that utilize wireless sensor and actuator networks. It is common in these systems that a sensor node needs not be continuously monitored, but communicates to the controller only at certain instances when it detects a disturbance event. In this paper, such a scenario is studied and particular emphasis is on efficient utilization of the shared communication resources. Encoder-decoder design for an event-based control system with the plant affected by pulse disturbances is considered. A new iterative procedure is proposed which can jointly optimize encoder-decoder pairs for a certainty equivalent controller. The goal is to minimize a design criterion, in particular, a linear quadratic cost over a finite horizon. The algorithm leads to a feasible design of time-varying non-uniform encoder-decoder pairs. Numerical results demonstrate significant improvements in performance compared to a system using uniform quantization., © 2006 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 20101221