Time-varying Wireless Channel Research Articles

RoCoMAR: Robots’ Controllable Mobility Aided Routing and Relay Architecture for Mobile Sensor Networks

In a practical deployment, mobile sensor network (MSN) suffers from a low performance due to high node mobility, time-varying wireless channel properties, and obstacles between communicating nodes. In order to tackle the problem of low network performance and provide a desired end-to-end data transfer quality, in this paper we propose a novel ad hoc routing and relaying architecture, namely RoCoMAR (Robots' Controllable Mobility Aided Routing) that uses robotic nodes' controllable mobility. RoCoMAR repeatedly performs link reinforcement process with the objective of maximizing the network throughput, in which the link with the lowest quality on the path is identified and replaced with high quality links by placing a robotic node as a relay at an optimal position. The robotic node resigns as a relay if the objective is achieved or no more gain can be obtained with a new relay. Once placed as a relay, the robotic node performs adaptive link maintenance by adjusting its position according to the movements of regular nodes. The simulation results show that RoCoMAR outperforms existing ad hoc routing protocols for MSN in terms of network throughput and end-to-end delay.

Energy Efficient MAC Protocol in Vehicular Networks

In VANETs the trade off between energy efficiency and throughput is one of the main constraints since the medium is time varying wireless channel. In this work we introduce fragmented transmission scheme in to VANETs that improve the energy efficiency pursuing high throughput. In existing systems contention window and back off stage is adapted according to mobility of vehicular node. Along with impact of mobility current channel state also considered in this paper to make the system energy efficient. The simulation results show that the proposed scheme improves throughput making the system energy efficient. General Terms Markov model, Access point (AP)

Efficient Resource Provisioning and Rate Selection for Stream Mining in a Community Cloud

Real-time stream mining such as surveillance and personal health monitoring, which involves sophisticated mathematical operations, is computation-intensive and prohibitive for mobile devices due to the hardware/computation constraints. To satisfy the growing demand for stream mining in mobile networks, we propose to employ a cloud-based stream mining system in which the mobile devices send via wireless links unclassified media streams to the cloud for classification. We aim at minimizing the classification-energy cost, defined as an affine combination of classification cost and energy consumption at the cloud, subject to an average stream mining delay constraint (which is important in real-time applications). To address the challenge of time-varying wireless channel conditions without a priori information about the channel statistics, we develop an online algorithm in which the cloud operator can dynamically adjust its resource provisioning on the fly and the mobile devices can adapt their transmission rates to the instantaneous channel conditions. It is proved that, at the expense of increasing the average stream mining delay, the online algorithm achieves a classification-energy cost that can be pushed arbitrarily close to the minimum cost achieved by the optimal offline algorithm. Extensive simulations are conducted to validate the analysis.

Energy-Efficient Transmissions of Bursty Data Packets with Strict Deadlines over Time-Varying Wireless Channels

We develop a novel approach to energy-efficient transmissions with arbitrary packet arrival process and strict delay constraints over time-varying wireless channels. When the arrivals, deadlines, and channel realizations are known a priori, we formulate the problem as a convex program. Relying on the specific structure of the optimality conditions, we put forth an efficient algorithm with a linear computational complexity in the order of constraint number to find the (offline) optimal rate control strategy. It is revealed that the power usage under the optimal policy admits a multi-level water-filling form, where the determination of the multiple water-levels can be visualized by the trajectory of letting a string tie its two ends and then taut between what we call the "water" arrival and departure curves. Guided by the optimal strategy, development of energy-efficient online schedules in practical systems is discussed. Numerical results are provided to demonstrate the merits of the proposed novel scheme.

Traffic-Aware Link Rate Adaptation for Multi-rate 802.11 Networks

802.11 networks provide multi-rate capability to offer rate adaptability against the time-varying wireless channel. However, how to switch between the available rates has not been standardized. Existing rate adaptation (RA) solutions assume common transmission power and can only passively tune link rate to match the inferred channel condition via different methods. This simple attitude is neither flexible in traffic-aware link rate selection nor effective in energy conservation and spatial reuse since transmission power may be either too low to sustain the link rate or too high that results in unnecessary energy consumption and worse spatial reuse. Different from existing solutions, we think that link rate switch should be driven by traffic load and power control should be considered with rate adaptation together to conserve energy and increase spatial reuse. To this end, we propose a traffic-aware link rate adaptation scheme (TARA) via power control for multi-rate 802.11 networks. Its basic idea consists of a two-step procedure. Firstly, traffic load is sensed in the MAC layer to decide whether link rate should be increased or decreased for the next transmission. Afterwards, power control is carried out in the PHY layer to guarantee that the new link rate can be sustained while minimizing the transmission power. Extensive simulation results show that TARA outperforms typical existing schemes in terms of energy efficiency and throughput.

Joint Time-Frequency Channel Estimation for Time Domain Synchronous OFDM Systems

As the key technology of Chinese national digital television terrestrial broadcasting (DTTB) standard, time domain synchronous OFDM (TDS-OFDM) has high spectral efficiency at the cost of performance loss over fast fading channels. In this paper, a novel time-frequency signal structure is proposed to improve the system performance of TDS-OFDM over fast time-varying channels. Each TDS-OFDM symbol adopts the time-domain one-sample shifted training sequence (TS) and the frequency-domain grouped pilots as the time-frequency training information. The modulable orthogonal sequence (MOS) with perfect autocorrelation property is adopted as the TS, while each pilot group has only one non-zero central pilot surrounded by several zero pilots. The corresponding joint time-frequency channel estimation utilizes the time-domain TS for path delay estimation and the frequency-domain grouped pilots for path gain estimation, thus accurate tracking of the fast time-varying wireless channel could be achieved. Only about 1% of the total subcarriers will be occupied by the redundant grouped pilots, thus the loss in spectral efficiency is negligible. Simulation results demonstrate that the proposed scheme outperforms the conventional solutions over fast fading channels.

Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels

Stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean-square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and nonresolvable multipath received signals are considered and represented as small-scaled Nakagami fading. The proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method’s viability and the results are presented.

Characterization of Non-Stationary Channels Using Mismatched Wiener Filtering

A common simplification in the statistical treatment of linear time-varying (LTV) wireless channels is the approximation of the channel as a stationary random process inside certain time-frequency regions. We develop a methodology for the determination of local quasi-stationarity (LQS) regions, i.e., local regions in which a channel can be treated as stationary. Contrary to previous results relying on, to some extent, heuristic measures and thresholds, we consider a finite-length Wiener filter as realistic channel estimator and relate the size of LQS regions in time to the degradation of the mean square error (MSE) of the estimate due to outdated and thus mismatched channel statistics. We show that for certain power spectral densities (PSDs) of the channel a simplified but approximate evaluation of the matched MSE based on the assumption of an infinite filtering length yields a lower bound on the actual matched MSE. Moreover, for such PSDs, the actual MSE degradation is upper-bounded and the size of the actual LQS regions is lower-bounded by the approximate evaluation. Using channel measurements, we compare the evolution of the LQS regions based on the actual and the approximate MSE; they show strong similarities.

Compressive Coded Modulation for Seamless Rate Adaptation

This paper presents a novel compressive coded modulation (CCM) which simultaneously achieves joint source-channel coding and seamless rate adaptation. The embedding of source compression into modulation brings significant throughput gain when the physical layer data contain non-negligible redundancy. The kernel of CCM is a new random projection (RP) code inspired by the compressive sensing (CS) theory. The RP code generates multilevel symbols from source binaries through weighted sum operations. Then, the generated RP symbols are mapped into a dense constellation for transmission. The receiver performs joint decoding based on received symbols. As the number of RP symbols can be adjusted in fine granularity, the rate adaptation becomes seamless. Two key design issues in the proposed CCM are addressed in this paper. First, we consider the RP code design for sources with different redundancies. Three principles are established and a concrete implementation is given. Second, we devise a linear-time decoding algorithm for the proposed RP code. In this belief propagation (BP) algorithm, we find that computing convolution in time domain is more efficient than that in frequency domain for binary variable nodes. Moreover, we invent a ZigZag deconvolution to further reduce the complexity. Analysis show that the proposed decoding algorithm is nearly 20 times faster than the state-of-the-art BP algorithm for CS called CS-BP. Emulations on traced data show that CCM achieves significant throughput gain, up to 33% and 70%, respectively, over the Hybrid ARQ with compression and BICM with compression, under practical time-varying wireless channels.

Reconfigurable performance measurement system-on-a-chip for baseband wireless algorithm design and verification

Modern wireless technology applies several powerful but complex techniques - such as multiple-antenna systems, orthogonal frequency-division multiplexing, and capacity-approaching forward error correcting codes - to provide reliable broadband digital communications over the time-varying mobile radio channel. Such techniques appear in most recent wireless standards such as IEEE 802.11n Wi-Fi, IEEE 802.16 WiMax, and 3GPP LTE. Bit error rate simulation continues to be the workhorse design verification and performance optimization methodology; however, the growing complexity of modern wireless systems and the tendency of wireless standards to evolve even after product development has started have greatly increased the required simulation times to the extent that software-based simulation is now the major bottleneck in wireless system development. This article describes how baseband performance verification of wireless systems can be accelerated by over four orders of magnitude using compact, accurate, and high-throughput emulators implemented on reconfigurable field programmable gate arrays.

Delay controlled proportional fair scheduling in Rayleigh fading wireless channel

In this study, the authors consider a delay control problem with proportional fair scheduling in time-varying wireless channels. For proportional fairness of transmission rates among users, a congestion control scheme is proposed for guaranteeing both throughput and delay of the wireless network. Specifically, a scheduling weight is introduced to control queue lengths without degrading the throughput of the network because the delay of users depends on their queue length. Using the asymptotic approximation technique, the throughput and delay performance of the proposed scheme are analysed and showed the multiuser diversity effect analytically in the Rayleigh-fading wireless channels. Finally, simulation results show that the proposed scheme improves delay without degrading throughput.

A Low-Cost Platform for Time-Variant Wireless Channel Measurements With Application to Positioning

Channel modeling for the application of positioning requires the knowledge of multipath characteristics and the absolute delay information of the line-of-sight signal. Additionally, a smooth time evolution of the channel impulse response is essential for tracking algorithms used for this application. Hence, an accurate position information of transmitter and receiver antennas in a dynamic scenario is a requirement for channel sounder measurements. This paper describes a low-cost measurement platform which is able to cope with this requirement. Moreover, an extension of the parameter estimation space by constructing a virtual antenna array in the case of single-input and single-output measurements is possible. Therefore, the 1-D angle of arrival, propagation path amplitude, and delay can be estimated jointly. The proposed measurement platform is validated based on measured channel sounder data. From the extracted data, we present statistical results that are important for the application of positioning, which is the non-light-of-sight bias including its spatial correlation coefficient and the angle of arrival of the first detected path.

Structural Solutions for Dynamic Scheduling in Wireless Multimedia Transmission

In this paper, we propose a systematic solution to the problem of scheduling delay-sensitive media data for transmission over time-varying wireless channels. We first formulate the dynamic scheduling problem as a Markov decision process that explicitly considers the users' heterogeneous multimedia data characteristics (e.g., delay deadlines, distortion impacts and dependences, and so on) and time-varying channel conditions, which are not simultaneously considered in state-of-the-art packet scheduling algorithms. This formulation allows us to perform foresighted decisions to schedule multiple data units for transmission at each time in order to optimize the long-term utilities of the multimedia applications. The heterogeneity of the media data enables us to express the transmission priorities between the different data units as a priority graph, which is a directed acyclic graph. This priority graph provides us with an elegant structure to decompose the multidata unit foresighted decision at each time into multiple single-data unit foresighted decisions which can be performed sequentially, from the high priority data units to the low priority data units, thereby significantly reducing the computation complexity. When the statistical knowledge of the multimedia data characteristics and channel conditions is unknown a priori, we develop a low-complexity online learning algorithm to update the value functions, which capture the impact of the current decision on the future utility. The simulation results show that the proposed solution significantly outperforms existing state-of-the-art scheduling solutions.

Optimal packet scheduling for energy harvesting sources on time varying wireless channels

In this paper, we consider a source node that operates over a time varying channel with energy harvesting capability. The goal of the source is to maximize the average number of successfully delivered packets per time slot. The source is able to choose whether to transmit a packet or defer the transmission in each time slot. The decision which is chosen by the source depends on the channel information available and the length of the energy queue. We formulate the problem of finding the optimal policy as a Markovian decision problem. We show some properties of the value function that represents the discounted number of successfully delivered packets per time slot. We prove that the optimal policy is a threshold type policy depending on the state of the channel and the length of the energy queue. We also derive an upper bound for the average number of packets per time slots successfully received by the destination. We show using numerical results that this bound is a tight bound on the performance of the optimal policy. And we consider the case of time varying channel but without channel state information (CSI). Then, we study the impact of channel time varying nature and the availability of CSI. In this case, we show that the optimal policy is a greedy policy. The performance of this greedy policy is also calculated.

Iterative Time-Variant Channel Estimation for 802.11p Using Generalized Discrete Prolate Spheroidal Sequences

This paper deals with channel estimation for orthogonal frequency-division multiplexing (OFDM) in time-variant wireless propagation channels. We particularly consider the challenges of the IEEE 802.11p standard, which is the worldwide dominant system for vehicular communications. For historic reasons, 802.11p uses a pilot pattern that is identical to the pattern used in 802.11a, which was initially designed for the estimation of indoor channels with little or no time variations. Therefore, this pilot pattern violates the sampling theorem for channels with both large delay spread and large Doppler spread, as often occurs in vehicular communications. To remedy this problem, we design a robust iterative channel estimator based on a 2-D subspace spanned by generalized discrete prolate spheroidal sequences. Due to the tight subspace design, the iterative receiver is able to converge to the same bit error rate (BER) as a receiver with perfect channel knowledge. Furthermore, we propose a backward compatible modification of the 802.11p pilot pattern such that the number of iterations sufficient for convergence can be reduced by a factor of 2-3, strongly reducing implementation complexity.

Time-Variant Radio Channel Characterization and Modelling of Vegetation Media at Millimeter-Wave Frequency

Results of an extensive measurement campaign to characterize and model dynamic effects on the radio channel in vegetation media at 40 GHz, are presented. Using two small trees in an anechoic chamber, narrowband fast-fading measurements, utilizing co-polarized signals, were conducted to obtain radio channel characterization. This was performed as a function of the bi-static scattering angle, wind speed, wind incidence, and tree species. Furthermore, a modelling methodology is investigated and assessed as to its feasibility as a means to model vegetation dynamics effects on propagation. A radio channel model based on a simplified set of Markovian parameters, is proposed. The model is representative of the radio signal in the three main identified propagation regions around a vegetation volume as a mean to satisfactorily model highly time-variant radio signals. The propagation regions considered are receiver angular sections (in the azimuth plane) around the tree, where the received signal behaves distinctly for each region. Model validation results are presented using one of the tree species.

Blind Recursive Subspace-Based Identification of Time-Varying Wideband MIMO Channels

We present a blind recursive algorithm for tracking rapidly time-varying wireless channels in precoded multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Subspace-based tracking is normally considered for slowly time-varying channels only. Due to the frequency correlation of the wireless channels, the proposed scheme can collect data not only from the time but from the frequency domain as well to speed up the update of the required second-order statistics. After each such update, the subspace information is recomputed using the orthogonal iteration, and then, a new channel estimate is obtained. We also investigate choices of precoder in terms of the tradeoff between the symbol recovery capability and the channel estimation performance and demonstrate the convergence properties of our approach. The proposed algorithm is evaluated in a Third-Generation Partnership Project (3GPP) Spatial Channel Model suburban macro scenario, in which a mobile station is allowed to move in any direction with a speed up to 100 km/h, corresponding to a maximum Doppler shift of about 230 Hz in this case. Numerical experiments show that the normalized mean square error of the channel estimates converges to a level of -30 dB within less than five OFDM symbols when the signal-to-noise ratio (SNR) (per symbol) is ≥ 20 dB.

Video streaming transmission: performance modelling over wireless local area networks under saturation condition

Transmitting delay-sensitive video streaming over IEEE 802.11e wireless local area networks (WLANs) is becoming increasingly popular. However, the transmission of real-time video streaming is very challenging because of the time-varying wireless channels and video content characteristics. The authors propose an accurate model to assess the perceived quality of video streaming over WLANs with enhanced distributed coordination function (EDCF) mechanism. The analytical model considers not only the packet loss caused by wireless interference and channel fading, but also the effects of loss from channel access competition. Based on the Markov chain, the authors then present the discrete probability distribution of medium access control (MAC) layer packet service time by using the signal transfer function of the generalised state transition diagram. Moreover, the coding relation of lost video frames is also explored in the performance analysis of the proposed model. Simulations based on Network Simulator 2 (NS-2) are conducted to verify the performance of the analytical model. The results show that the proposed model provides superior accuracy for the perceived quality of MPEG-4 video streaming over IEEE 802.11e EDCF-based WLANs.

A method of ICI cancellation for OFDM with delay diversity

In orthogonal frequency division multiplexing (OFDM) system, the time variation of a wireless channel destroys orthogonality among the sub-carriers, and this induces inter-carriers interference (ICI) and degrades system performance severely in mobile environment. In this paper, a new method of ICI cancellation based on delay diversity (DD) was proposed, which provides a way to mitigate the negative effect from the time variation of the wireless paths, thus improve the system performance greatly. The new method was called time-domain self-interference cancellation (TDSIC) algorithm, which is different from other existing methods, such as frequency-domain method. In a cyclically extended OFDM system, the fading characteristics of extended OFDM symbols with different cyclic delay are different with each other, so in our TDSIC method, a new diversity collection scheme at the receiver end is proposed, which can be used to improve the system performance by suppressing ICI through selecting appropriate parameters. Moreover, the cyclically extended OFDM symbol at the transmitter side and diversity collection with different delay added OFDM symbols at the receiver side are used in the TDSIC method with the tradeoff of time-expense, so the well-known fixed delay for symbol at the transmitter side may be detected by the receiver side through estimating several parameters of wireless channels. In summary, the key of the TDSIC method is to improve the system performance with the cost of time. Based on performance analysis, simulation has proved that TDSIC may effectively improve the performance of the time-variant wireless channel.

Strider

This paper presents the design, implementation and evaluation of Strider, a system that automatically achieves almost the optimal rate adaptation without incurring any overhead. The key component in Strider is a novel code that has two important properties: it is rateless and collision-resilient . First, in time-varying wireless channels, Strider's rateless code allows a sender to effectively achieve almost the optimal bitrate, without knowing how the channel state varies. Second, Strider's collision-resilient code allows a receiver to decode both packets from collisions, and achieves the same throughput as the collision-free scheduler. We show via theoretical analysis that Strider achieves Shannon capacity for Gaussian channels, and our empirical evaluation shows that Strider outperforms SoftRate, a state of the art rate adaptation technique by 70% in mobile scenarios and by upto 2.8× in contention scenarios.