Conventional Adaptive Schemes Research Articles

Development of a Distributed Adaptive Dual MPC Scheme with Application to Control of an Octuple Tank System

The distributed model predictive control (dMPC) provides a computationally efficient framework for designing controllers for a large dimensional plant. The performance of such dMPC scheme critically depends upon the quality of the control relevant models used for predictions. In continuously operated processes, model plant mismatch (MPM) arises due to the time-varying nature of process parameters and shift in the operating conditions due to economic considerations and this results in performance degradation. Recently an adaptive version of dMPC (dAMPC) has been developed that achieves better control performance using online model parameter update. A conventional adaptive MPC scheme, however, requires external dither signal to be injected to generate sufficient excitation needed for parameter estimation. In this work, dAMPC is cast in the dual control framework (dADMPC) which ensured sufficient input excitation as and when needed for better online parameter estimation. The proposed controller is based on black-box models parameterized using generalized orthogonal basis filters (GOBF). The Fourier coefficients of the GOBF models are dynamically updated online using recursive parameter estimators to account for MPM. The efficacy of the proposed scheme is demonstrated by simulating servo and regulatory problems associated with the benchmark octuple tank process. The simulation study reveals that performance of the proposed dADMPC scheme is comparable to a centralized ADMPC while achieving a considerable reduction in the online computation time.

Robust adaptive Bayesian beamforming against stationary and nonstationary interferences

In this work, we aim to enhance the robustness of conventional adaptive beamforming schemes against both signal steering vector uncertainties and interference nonstationarity here. For this purpose, a random model with Watson prior distribution is applied to the steering vector of interest, and cluster structured prior belief about the interferer motion is incorporated into the statistical analysis. However, the difficulty in handling the normalization factor of the Watson distribution makes the Bayesian inference of this probabilistic model prohibitive. Towards this end, an efficient algorithm using variational Bayesian expectation-maximization is proposed, by iteratively majorizing a lower bound on the variational free energy to refine the latent parameters and circumvent intractable moment computation. A specific beamformer encompasses a trade-off among accuracy, speed and ease of implementation is thus obtained. Further, an extension of the algorithm to the case of moving interferences is presented by assigning a Dirichlet process prior to the hidden parametric space. By doing so, the underlying time-aware clusters embedded in the interference-plus-noise vectors can be automatically revealed. Both simulated and experimental results validate the superiority of the algorithms over the existing algorithms.

A Time Delay Estimation Based Adaptive Sliding Mode Strategy for Hybrid Impedance Control

This paper is inspired by the automation of cleaning tasks required inside the endogenous environment. This work intends to develop a robust adaptive strategy for force-position control, using robotic manipulators. With this objective, the operational/task space is decoupled into two sub-spaces, and the impedance model for the manipulator is designed using the standard second-order filters. The impedance filter generates the reference commands for the inner loop, which assures bounded position and force tracking. A delay estimation based adaptive sliding mode strategy is proposed for carrying out the tracking objective, and its convergence is proved using the Lyapunov-Razumikhin theorem. The controller uses past data to estimate the uncertainties in the error dynamics and exploits the sliding mode strategy to provide robustness in the closed-loop. This technique circumvents the under/overestimation issues, and linear/nonlinear parametrization requirements in conventional adaptive schemes. Multiple numerical simulations and experiments are performed, and the results point to the validity of the proposed control law in real-world settings.

Symplectic integration with non-canonical quadrature for guiding-center orbits in magnetic confinement devices

We study symplectic numerical integration of mechanical systems with a Hamiltonian specified in non-canonical coordinates and its application to guiding-center motion of charged plasma particles in magnetic confinement devices. The technique combines time-stepping in canonical coordinates with quadrature in non-canonical coordinates and is applicable in systems where a global transformation to canonical coordinates is known explicitly but its inverse is not. A fully implicit class of symplectic Runge-Kutta schemes has recently been introduced and applied to guiding-center motion by Zhang et al. (2014) [9]. Here a generalization of this approach with emphasis on semi-implicit partitioned schemes is described together with methods to enhance performance, in particular avoiding evaluation of non-canonical variables at full time steps. For application in toroidal plasma confinement configurations with nested magnetic flux surfaces a global canonicalization of coordinates for the guiding-center Lagrangian by a spatial transform is presented that allows for pre-computation of the required map in a parallel algorithm in the case of time-independent magnetic field geometry. Guiding-center orbits are studied in stationary magnetic equilibrium fields of an axisymmetric tokamak and a realistic three-dimensional stellarator configuration. Superior long-term properties of symplectic methods are demonstrated in comparison to a conventional adaptive Runge-Kutta scheme. Finally statistics of fast fusion alpha particle losses over their slowing-down time are computed in the stellarator field on a representative sample, reaching a speed-up of the symplectic Euler scheme by more than a factor three compared to usual Runge-Kutta schemes while keeping the same statistical accuracy and linear scaling with the number of computing threads.

Energy Efficient and Throughput Optimal CSMA Scheme

Carrier sense multiple access (CSMA) is widely used as a medium access control (MAC) in wireless networks due to its simplicity and distributed nature. This motivated researchers to find CSMA schemes that achieve throughput optimality. In 2008, it has been shown that a simple CSMA-type algorithm is able to achieve optimality in terms of throughput and has been given the name “adaptive” CSMA. Later, new technologies emerged where a prolonged battery life is crucial such as environment and industrial monitoring. This inspired the foundation of new CSMA-based MAC schemes, where links are allowed to transition into a sleep mode to reduce the power consumption. However, the throughput optimality of these schemes was not established. This paper, therefore, aims to find a new CSMA scheme that combines both throughput optimality and energy efficiency by adapting to the throughput and power consumption needs of each link. This is done by controlling operational parameters, such as back-off and sleeping timers, with the aim of optimizing a certain objective function. The resulting CSMA scheme is characterized by being asynchronous, completely distributed and being able to adapt to different power consumption profiles required by each link while still ensuring throughput optimality. The performance gain in terms of energy efficiency compared with the conventional adaptive CSMA scheme is demonstrated through computer simulations.

Sample-based adaptive Kalman filtering for accurate camera pose tracking

Inferring the camera pose with high accuracy is deemed crucial in many applications such as robot manipulation and virtual reality. Traditionally, features extracted from camera images are processed by Kalman-based schemes due to their high efficacy and fast response. Yet, the performance of the filter deteriorates if the parameters of the filter are uncertain. Estimating the noise parameters through conventional adaptive schemes alleviates this problem, yet the estimation’s accuracy still suffers from rough parameter estimations. To improve the accuracy of pose estimations further, this work proposes a novel adaptive scheme which employs a multi-model approach to approximate the system posteriori via sampling the noise and initial state covariance priories and progressively adjusting the filter parameters using the drawn samples. The experimental results confirm the enhanced performance of the proposed adaptive method compared to previously applied adaptive and non-adaptive pose estimation schemes, at the expense of additional complexity.

An Enhanced Adaptive Scheme With Pairwise Coding for OFDM-VLC System

For a visible light communication (VLC) system, different modulation formats and coding schemes are considered as the effective way to improve system performance under the limited bandwidth of light emitting diode. In this letter, we propose and experimentally demonstrate an enhanced adaptive scheme with pairwise coding (PWC) for an orthogonal frequency-division multiplexing (OFDM)-VLC system. Due to its no coding overhead and low complexity, it can be used to enhance the performance of the OFDM-VLC system. Through pairing the good and bad subcarriers, the signal-to-noise ratio (SNR) imbalance of this pair subcarrier is mitigated. Hence, it can lower the required SNR for a certain bit error ratio (BER). In the enhanced adaptive scheme with PWC, the low-frequency subcarriers (SCs) are modulated by 16 quadrature amplitude modulation (16QAM), while the high-frequency SCs are modulated by 4QAM, and in the midst of them, 32QAM is used. The experimental results show that, it can achieve 1.1 dB Q 2 factor improvement compared with the conventional adaptive scheme and the BER can be up to 1.66×10 -5 using the proposed adaptive scheme with PWC.

Delay-QoS-Aware Adaptive Modulation and Power Allocation for Dual-Channel Coherent OWC

Statistical-delay quality of service (QoS) provides bounded link-layer delay over wireless fading channels with a certain delay-bound violation probability. We propose statistical-delay-QoS-aware adaptive modulation (AM) and power allocation for a dual-channel coherent optical wireless communication system over the atmospheric turbulence fading channels. For given statisticaldelay constraints and target bit-error-rate requirements, our proposed AM and power allocation maximize the effective spectral efficiency subject to the transmit-power constraints. We develop delay-QoS-aware adaptive transmission schemes by employing independent and joint channel optimizations subject to average transmit-power constraints. We also consider independent, joint, and successive channel optimizations for developing delay- QoS-aware adaptive transmission schemes subject to peak transmit-power constraints. Numerical results demonstrate that our proposed AM and power allocation significantly outperform the conventional adaptive transmission schemes in the strict statistical-delay constraints. Numerical results also depict superiority of the joint channel optimization in the strong turbulence fading and strict statistical-delay constraints.

Conditional Power and Rate Adaptation for MQAM/OFDM Systems Under CFO With Perfect and Imperfect Channel Estimation Errors

In this paper, a new conditional power and rate adaptation scheme for orthogonal frequency-division multiplexing (OFDM) systems is proposed in the presence of carrier frequency offset (CFO), with perfect and imperfect channel state information (CSI). The conventional adaptive scheme is shown to be a special case of the conditionally adaptive scheme technique that enables the resulting nonconvex optimization problem, which is solved in a feasible way. It leads to a solution for optimal power adaptation that maximizes the spectral efficiency of an OFDM system using $M$ -ary quadrature amplitude modulation (MQAM) under average power and instantaneous bit error rate (BER) constraints. Closed-form expressions for the average spectral efficiency (ASE) of adaptive OFDM systems are derived for perfect and imperfect CSI cases. The theoretical results and computer simulations show that range of the conditional adaptation becomes narrow and the performance of constant power and continuous rate is very close to that of the conditionally adaptive power and continuous rate for higher CFO or high signal-to-noise ratio (SNR) values.

Practical Transmission Scheme With Fixed Communication Rate Under Constraints of Transmit Power and Secrecy Outage Probability

The issue of physical layer security in single-antenna wiretap channels with slow fading is addressed in this letter. With the assumption of perfect channel state information (CSI) about the main channel and statistical CSI about the eavesdropper's channel, we propose a new secure transmission scheme under the constraints of transmit power and secrecy outage probability (SOP). This scheme fixes the communication rate and adaptively adjusts the secrecy rate and the transmit power during transmission, which is different from the conventional adaptive and non-adaptive schemes in the literature. By fixing the communication rate, the proposed scheme fixes the length of codebook and thus simplifies the codebook design. Simulation results show that the proposed scheme performs well when the SOP constraint is strict.

DFT Precoded OFDM—An Alternative Candidate for Next Generation PONs

Recently, the orthogonal frequency division multiplexing (OFDM) technique has been extensively studied for fiber-based optical transmissions in the context of access networks. The adaptive modulation optical (AMO) OFDM system has been proved to be one of the cost-effective solutions. Among adaptive modulation techniques, the Levin-Campello (LC) bit/power loading, which is widely implemented for xDSL systems, is shown to bring excellent performances in unamplified optical intensity modulated/direct detected (IMDD) transmissions. In this paper a novel adaptive discrete Fourier transform precoded OFDM (POFDM) is proposed and investigated. By means of numerical simulation, the proposed modulation scheme is shown to reduce the peak-to-average power ratio of the transmitted OFDM signal up to 2 dB at 10 -3 clipping rate. As a consequence, a smaller input back-off can be applied to the laser-driving current before the power amplifier, resulting in a lower power consumption of the POFDM system when compared to the conventional LC AMOOFDM system. According to simulation results, the energy consumption of the power amplifier is reduced by a factor of two in unamplified optical IMDD transmissions. Moreover, in terms of capacity-versus-reach performance, the proposed system achieves the same performance as the conventional adaptive modulation scheme.

차량 애드혹 네트워크에서 효과적인 상황 인지를 위한 이중 비콘 전송 기법

차량 애드혹 네트워크에서 비콘 전송은 가장 기본적인 메커니즘 중 하나이다. 차량 통신 시스템에서는 각 노드들의 비콘 교환을 통하여 주변 상황 인지를 비롯한 다양한 통신 서비스가 구현된다. 본 논문에서는 기존의 단일 비콘 전송 방식에서 벗어난 이중 비콘 전송 방식을 제안한다. 이중 비콘 전송 방식은 일반적으로 통신 시스템에서 고려되는 비콘을 차량 통신 시스템에 특화시켜 안전 서비스를 위한 비콘과 편의 서비스를 위한 비콘 두 가지 기능으로 나누어 각 기능에 따라 통신 파라미터를 분산시켜 적용하는 방식이다. 이러한 비콘 메커니즘의 성능을 평가하기 위하여 가장 대표적인 성능 지표인 거리에 따른 비콘 패킷 수신율을 실험, 제안하는 이중 비콘 전송 방식의 우수함을 검증하였다. 결론적으로 이중 비콘 전송 방식은 단일 비콘 전송 방식에 비하여 채널에 부하를 줄임과 동시에 더욱 넓은 통신 반경과 원활한 상황 인지 서비스를 가능하게 한다. 덧붙여, 제안하는 이중 비콘 전송 방식은 실제로 구현함에 있어서 복잡성이 적고, 다른 적응형 비콘 전송 방식을 함께 적용 가능하기 때문에 효용성이 뛰어나다. Beacon transmission is one of the fundamental mechanisms in vehicular ad hoc networks. Variety services including context awareness can be embodied by exchanging beacons in each vehicle. In this paper, we propose dual beacon transmission instead of traditional single beacon transmission for beaconing mechanism. dual beacon transmission divides beacon into two functions and operates two beaconing process independently. We verified the superiority of dual beacon transmission by comparing beacon packet delivery ratio with single beacon transmission. In conclusion, dual beacon transmission can reduce channel load and have both wider communication range and effective context awareness. In addition, implementing dual beacon transmission has less complexity and appliable with conventional adaptive beaconing schemes.

Path-Congestion-Aware Adaptive Routing With a Contention Prediction Scheme for Network-on-Chip Systems

Network-on-chip systems can achieve higher performance than bus systems for chip multiprocessor systems. However, as the complexity of the network increases, the channel and switch congestion problems become major performance bottlenecks. An effective adaptive routing algorithm can help minimize path congestion through load balancing. However, conventional adaptive routing schemes only use channel-based information to detect the congestion status. Due to the lack of switch-based information, channel-based information is difficult to reveal the real congestion status along the routing path. Therefore, in this paper, we remodel the path congestion information to show hidden spatial congestion information and improve the effectiveness of routing path selection. We propose a path-congestion-aware adaptive routing (PCAR) scheme based on the following techniques: 1) a path-congestion-aware selection strategy that simultaneously considers switch congestion and channel congestion, and 2) a contention prediction technique that uses the rate of change in the buffer level to predict possible switch contention. The experimental results show that the proposed PCAR scheme can achieve a high saturation throughput with an improvement of 15.4%-48.7% compared to existing routing schemes. The proposed PCAR method also includes a VLSI architecture, which has higher area efficiency with an improvement of 16%-35.7% compared with the other router designs.

Joint Rate Adaptation and Best-Relay Selection Using Limited Feedback

This paper presents a novel joint rate adaptation and relay selection scheme for multi-relay networks adopting half-duplex best-relay decode-and-forward protocol. The proposed scheme aims to maximize the overall transmission rate when relays are allowed to forward messages using different rates from the source. It is shown that the proposed scheme outperforms the conventional adaptive scheme in terms of the spectral efficiency (e.g. by 10.1% improvement for SNR=10 dB). Furthermore, in order to reduce signaling overhead of the proposed scheme, a number of joint discrete-rate adaptation and relay selection approaches are proposed for both non-reciprocal and reciprocal channels. The relay selection is basically a two-stage scheme. At the rm first stage, a set of relays are selected based on mixed channel quality information (CQI), i.e., the knowledge of CQI varies for different links; at the second stage, the best relay within the set is selected based on instantaneous CQI, which is obtained through carefully designed signaling protocols. It is shown that the proposed discrete-rate adaptation schemes can offer comparable spectral efficiency to the conventional adaptive scheme with significantly reduced signaling overhead.

On quality of experience of scalable video adaptation

In this paper, we study the quality of experience (QoE) issues in scalable video coding (SVC) for its adaptation in video communications. A QoE assessment database is developed according to SVC scalabilities. Based on the subjective evaluation results, we derive the optimal scalability adaptation track for the individual video and further summarize common scalability adaptation tracks for videos according to their spatial information (SI) and temporal information (TI). Based on the summarized adaptation tracks, we conclude some general guidelines for the effective SVC video adaptation. A rate-QoE model for SVC adaptation is derived accordingly. Experimental results show that the proposed QoE-aware scalability adaptation scheme significantly outperforms the conventional adaptation schemes in terms of QoE. Moreover, the proposed QoE model reflects the rate and QoE relationship in SVC adaptation and thus, provides a useful methodology to estimate video QoE which is important for QoE-aware scalable video streaming.

An Adaptive Hierarchical QAM Scheme for Enhanced Bandwidth and Power Utilization

Hierarchical quadrature amplitude modulation (HQAM) enables unequal priority transmission through the use of non-uniformly spaced constellations. In this paper, we propose an adaptive HQAM (A-HQAM) scheme where the ratios between the constellation distances are regularly adjusted based on the channel condition with the objective of maximizing the transmission efficiency. The source bit stream is divided into multiple sub-streams which are simultaneously transmitted, each on a different priority level. When using A-HQAM, the high priority sub-stream maintains an acceptable bit error rate performance over all channel conditions. As the channel condition improves, the required protection for the high priority sub-stream is reduced allowing for increasing the protection level of lower priority sub-streams. Hence, the number of sub-streams with acceptable BER performances is incrementally increased as the channel condition improves. Analysis and simulation results show that the proposed A-HQAM not only enhances the transmission efficiency but also provides reduced peak to average power ratio (PAPR). The proposed scheme offers reduced complexity by using one constellation size, unlike conventional adaptive schemes which require the use of several constellation sizes. Moreover, a practical A-HQAM implementation is presented which enables the receiver to successfully demodulate the received signal without knowing the varying transmission parameters.

Robust design of nonlinear internal models without adaptation

We propose a solution to the problem of semiglobal output regulation for nonlinear minimum-phase systems driven by uncertain exosystems that does not rely upon conventional adaptation schemes to estimate the frequency of the exogenous signals. Rather, the proposed approach relies upon regression-like arguments used to derive a nonlinear internal model able to offset the presence of an unknown number of harmonic exogenous inputs of uncertain amplitude, phase and frequency. The design methodology guarantees asymptotic regulation if the dimension of the regulator exceeds a lower bound determined by the actual number of harmonic components of the exogenous input. If this is not the case, a bounded steady-state regulation error is ensured whose amplitude, though, can be arbitrarily decreased by acting on a design parameter of the regulator.

Multistage adaptive filtering for identification of page-oriented volume holographic memories

Page-oriented volume holographic memories (POVHM) is a quadratically nonlinear channel because of the intensity detection at its output. To combat the two-dimensional intersymbol interference in a high-capacity POVHM, equalization of the output intensity array requires identification of the quadratic and possibly spatially varying impulse response of the channel. Although conventional adaptive filtering schemes are devised for identification of linear channels, they also require the length of the impulse response to be known in advance. In this work, we develop multistage quadratic normalized least mean square (LMS) (MS-QNLMS) adaptive filtering and multistage Volterra normalized LMS (MS-VNLMS) filtering to estimate the channel under quadratic nonlinearity, which do not require the support or length of the impulse response to be known a priori. By employing extensive numerical experiments, we provide performance and convergence comparisons of the proposed schemes with respect to a true-order quadratic estimator. We also show that MS-QNLMS filtering has less computational complexity and converges faster and more robust to various channel parameters as compared to MS-VNLMS.

Space-time cooperative diversity scheme using full feedback

This article proposes a new space-time cooperative diversity scheme called full feedback-based cooperative diversity scheme (FFBCD). In contrast to the conventional adaptive space-time cooperative diversity schemes that utilize the feedback from only the destination node, the new scheme utilizes the feedback from both the destination node and the cooperation node. With the feedback from the destination node, the occasional successful reception of the destination node in the information distribution stage can be detected, thus avoiding unnecessary retransmissions in the information delivery stage. The feedback from the cooperation node indicates the receiving state of the cooperation node in the information distribution stage, and the source node and the cooperation node will not perform cooperative retransmission during the information delivery stage unless the cooperation node is received successfully in the information distribution stage. In this way the new scheme can reduce the number of transmission attempt and improve the channel utilization. The expressions of the average number of transmission attempt are given. Numerical approximations and simulation results both show that the new scheme performs better than the non-cooperative scheme and the conventional adaptive space-time cooperative diversity scheme.

Adaptive pseudo-noise code acquisition scheme using automatic censoring for DS/SS communication in frequency-selective Rayleigh fading channel

An adaptive pseudo-noise code acquisition scheme based on automatic multipath signal cancellation for mobile communication systems in frequency-selective Rayleigh fading channel is proposed. The proposed system combines a serial strategy and an automatic censored cell-averaging constant false alarm rate (CFAR) detector based on ordered data variability. This system does not require any a priori information about the number of interferences caused by the presence of multipath signals in the reference channel. The mean acquisition time and the detection performances of the proposed processor are evaluated and compared with those of the conventional adaptive acquisition scheme based on fixed-censoring point detector. It is shown that the considered scheme outperforms significantly the conventional one. The effects of various channel parameters on the acquisition performance, namely the number of resolvable paths, the partial correlation length and the signal-to-noise ratio are also investigated.