Non-adaptive Schemes Research Articles

A novel low‐complexity transmission power adaptation in MC‐CDMA systems with a‐MRC receiver over Nakagami‐m fading channels

AbstractIn this paper, we propose a novel low‐complexity transmission power adaptation with good bit error rate (BER) performance for multicarrier code‐division multiple‐access (MC‐CDMA) systems over Nakagami‐m fading channels. We first propose a new receiver called ath‐order‐maximal‐ratio‐combining (a‐MRC) receiver with which the receiver power gain for the nth subcarrier is the ath (a⩾1) power of the corresponding channel gain. Incorporating the a‐MRC receiver, we then propose a new transmission power adaptation scheme where the transmission power is allocated over all the N subcarriers according to the subchannel gains and the transmitter adapts its power to maintain a constant signal‐to‐interference‐plus‐noise (SINR) at the receiver. The proposed scheme has a significant performance gain over the nonadaptive transmission scheme over both independent and correlated fading channels. Moreover, the proposed scheme keeps good BER performance while it is much simpler than the previous power control/adaptation schemes. Copyright © 2008 John Wiley & Sons, Ltd.

Cross-Layer Rate and Power Adaptation Strategies for IR-HARQ Systems over Fading Channels with Memory: A SMDP-Based Approach

Incremental-redundancy hybrid automatic repeat- request (IR-HARQ) schemes are proposed in several wireless standards for increased throughput-efficiency and greater reliability. We investigate transmit power and modulation order adaptation strategies for the IR-HARQ schemes over correlated Rayleigh fading channels using semi-Markov decision process-based model. In order to jointly analyze physical layer and link layer, transmitter model incorporates a finite-size buffer that receives randomly varying traffic from a higher layer application. It is assumed that channel variations can be modeled with a first-order Markov chain. We show that the optimal transmission power and rate adaptation laws under buffering delay and packet overflow constraints can be obtained using the framework of semi-Markov decision process. We discuss three different adaptation models for the IR-HARQ schemes and compare their performances with the non-adaptive scheme. It is shown that unique optimal policy exists for each case and it can be computed using linear programming approach. This optimal policy is then applied for realistic channel fading and incoming traffic samples to evaluate its performance for both hard-decision and soft-decision decoding. Simulation results in general point out that substantial power savings can be achieved using adaptation and also if the transmission-delay requirements are relaxed.

Patient-adapted reconstruction and acquisition dynamic imaging method (PARADIGM) for MRI

Dynamic magnetic resonance imaging (MRI) is a challenging problem because the MR data acquisition is often not fast enough to meet the combined spatial and temporal Nyquist sampling rate requirements. Current approaches to this problem include hardware-based acceleration of the acquisition, and model-based image reconstruction techniques. In this paper we propose an alternative approach, called PARADIGM, which adapts both the acquisition and reconstruction to the spatio-temporal characteristics of the imaged object. The approach is based on time-sequential sampling theory, addressing the problem of acquiring a spatio-temporal signal under the constraint that only a limited amount of data can be acquired at a time instant. PARADIGM identifies a model class for the particular imaged object using a scout MR scan or auxiliary data. This object-adapted model is then used to optimize MR data acquisition, such that the imaging constraints are met, acquisition speed requirements are minimized, essentially perfect reconstruction of any object in the model class is guaranteed, and the inverse problem of reconstructing the dynamic object has a condition number of one. We describe spatio-temporal object models for various dynamic imaging applications including cardiac imaging. We present the theory underlying PARADIGM and analyze its performance theoretically and numerically. We also propose a practical MR imaging scheme for 2D dynamic cardiac imaging based on the theory. For this application, PARADIGM is predicted to provide a 10–25 × acceleration compared to the optimal non-adaptive scheme. Finally we present generalized optimality criteria and extend the scheme to dynamic imaging with three spatial dimensions.

Adaptive Godunov-Based Model for Flood Simulation

Godunov-based shallow-water models utilize a discontinuous reconstruction of data at cell faces even for smooth flow, which can cause energy dissipation and degrade accuracy. Analysis of discrete equations shows that jumps (and therefore error) can be minimized by adaptively selecting either primitive or conservative variables for slope limiting and reconstruction according to the local Froude number. Therefore, a Godunov-based model with an adaptive scheme of slope limiting and variable reconstruction is presented. Two practical flood modeling applications are used to compare the performance of the adaptive scheme against two nonadaptive schemes. In addition, performance of second-order accurate schemes is compared to first-order schemes that utilize a second-order accurate description of terrain. Results show that the first-order adaptive scheme possesses the best combination of robustness, efficiency, and accuracy of the models tested.

High rate acoustic communications based on orthogonal frequency division multiplexing

Orthogonal frequency division multiplexing (OFDM) offers simplicity of FFT-based implementation with frequency-domain channel equalization, and has emerged as a standard in many terrestrial systems. Its application to underwater systems, however, is challenged by the motion-induced Doppler distortion, which creates nonuniform frequency offset in a wideband acoustic signal. To counteract this problem, recent research has focused on synchronization methods, demonstrating the feasibility of wideband OFDM in initial sea trials. We consider the design of a complete OFDM receiver based on three key techniques: adaptive carrier tracking, spatial diversity combining, and sparse channel estimation. In particular, we focus on time-domain channel estimation, which provides a natural platform for channel sparsing. Sparsing of the impulse response, or discarding of its insignificant coefficients, is shown to offer performance gains on acoustic channels, since they are often naturally sparse. Decision-directed operation, which is made possible by adaptive carrier tracking, yields a low overhead, and further improves the performance of channel estimation beyond that of nonadaptive pilot-based schemes. The technique proposed is applied to experimental data recorded in a shallow water channel over 1 km. Results show excellent performance of coded OFDM signals, transmitted in the 19-31 kHz band with a varying number of subcarriers.

SmartMIMO: An Energy-Aware Adaptive MIMO-OFDM Radio Link Control for Next-Generation Wireless Local Area Networks

Multiantenna systems and more particularly those operating on multiple input and multiple output (MIMO) channels are currently a must to improve wireless links spectrum efficiency and/or robustness. There exists a fundamental tradeoff between potential spectrum efficiency and robustness increase. However, multiantenna techniques also come with an overhead in silicon implementation area and power consumption due, at least, to the duplication of part of the transmitter and receiver radio front-ends. Although the area overhead may be acceptable in view of the performance improvement, low power consumption must be preserved for integration in nomadic devices. In this case, it is the tradeoff between performance (e.g., the net throughput on top of the medium access control layer) and average power consumption that really matters. It has been shown that adaptive schemes were mandatory to avoid that multiantenna techniques hamper this system tradeoff. In this paper, we derive smart MIMO: an adaptive multiantenna approach which, next to simply adapting the modulation and code rate as traditionally considered, decides packet-per-packet, depending on the MIMO channel state, to use either space-division multiplexing (increasing spectrum efficiency), space-time coding (increasing robustness), or to stick to single-antenna transmission. Contrarily tomany of such adaptive schemes, the focus is set on using multiantenna transmission to improve the link energy efficiency in real operation conditions. Based on a model calibrated on an existing reconfigurable multiantenna transceiver setup, the link energy efficiency with the proposed scheme is shown to be improved by up to 30% when compared to nonadaptive schemes. The average throughput is, on the other hand, improved by up to 50% when compared to single-antenna transmission.

Adaptive Bandwidth Management and Joint Call Admission Control to Enhance System Utilization and QoS in Heterogeneous Wireless Networks

The coexistence of different cellular networks in the same area necessitates joint radio resource management for enhanced QoS provisioning and efficient radio resource utilization. We propose adaptive bandwidth management and joint call admission control (JCAC) scheme for heterogeneous cellular networks. The objectives of the proposed adaptive JCAC scheme are to enhance average system utilization, guarantee QoS requirements of all accepted calls, and reduce new call blocking probability and handoff call dropping probability in heterogeneous wireless networks. We develop a Markov chain model for the adaptive JCAC scheme and derive new call blocking probability, handoff call dropping probability, and average system utilization. Performance of the proposed adaptive JCAC scheme is compared with that of nonadaptive JCAC scheme in the same heterogeneous wireless network. Results show an improvement in average system utilization of up to 20%. Results also show that connection-level QoS can be significantly improved by using the proposed adaptive JCAC scheme.

Transmission Power Adaptations in Multicarrier CDMA Communications Over Rayleigh-Fading Channels

We consider transmission power adaptations in multicarrier code-division multiple-access communications, where the transmission power is adapted in frequency and/or time domain in response to channel variations. With frequency-domain power adaptation, we propose to allocate the transmission power over N' (1 les N' les N) strongest subcarriers (which have the highest channel gains) rather than over all possible N subcarriers. We examine the effect of choosing N' on the performance of the frequency-domain power adaptation scheme and find that there exists an optimal N' that minimizes the average bit error rate (BER). In the time domain, we consider adapting the transmission power so that the desired signal strength at the receiver output remains at a fixed level. We analyze the BER performances of frequency-, time-, and combined frequency-time-domain power adaptations with an average transmission power constraint. Our results show that the frequency-and time-domain power adaptation schemes outperform the nonadaptive (i.e., constant uniform power over all subcarriers) scheme, particularly for the noise-and interference-limited regions, respectively. The combined frequency-time-domain power adaptation is shown to have a significant performance gain over the power adaptation in only the frequency or time domain, as well as over the nonadaptive scheme. We also present numerical results to investigate the effect of channel estimation error on the performance of the proposed power adaptation schemes.

Rotating machinery fault diagnosis using signal-adapted lifting scheme

Wavelet transform has been widely used for vibration-based machine fault diagnosis. However, it is a difficult task to choose or design appropriate wavelet or wavelets for a given application. In this paper, a new signal-adapted lifting scheme for rotating machinery fault diagnosis is proposed, which allows us to construct a wavelet directly from the statistics of a given signal. The prediction operator based on genetic algorithms is designed to maximize the kurtosis of detail signal produced by the lifting scheme, and the update operator is designed to minimize a reconstruction error. The signal-adapted lifting scheme is applied to analyze bearing and gearbox vibration signals. The conventional diagnosis techniques and non-adaptive lifting scheme are also used to analyze the same signals for comparison. The results demonstrate that the signal-adapted lifting scheme is more effective in extracting inherent fault features from complex vibration signals.

On Analysis and Design of Low Density Generator Matrix Codes for Continuous Phase Modulation

We investigate the analysis and design of low density generator matrix (LDGM) codes for continuous phase modulation (CPM). The system uses LDGM codes as an outer code for CPM. For additive white Gaussian noise channels, we derive the union bound to analyze the error floor performance. Design principles for lowering error floors are suggested from this analysis. We propose a design approach of jointly considering the LDGM code degree and the CPM modulation index. Then we consider the rate-adaptive system for slowly fading channels. By changing the rate of the LDGM codes, the information rate of the CPM signals is adapted according to channel variations. We use a low-rate LDGM code as the mother code. Higher rates are achieved by puncturing the output of these codes. To exploit the rate-flexible property of punctured LDGM codes, a rate function is proposed to calculate the rate of each transmitted block. Thus, we can have a quasi-continuous information rate. Numerical results show that this approach can improve the energy efficiency from a discrete-rate adaptation. Using the rate-adaptive approach, up to 11 dB transmitted energy gain can be achieved from the non-adaptive scheme in the low bit-error-rate region (smaller than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ) for minimum shift keying (MSK).

Adaptive DS/CDMA Packet Radio Communications over Indoor Multipath Fading Channels

In this paper, we propose an adaptive data transmission scheme for DS/CDMA packet radio communication systems in bandlimited indoor multipath fading channels. We first analyze the relationship between the code rate and the processing gain (defined as the number of chips per coded bit) in maximizing the normalized throughput in connection with the channel state of the indoor multipath fading channels. One observation made is that the maximum throughput with BPSK modulation is attained when the code rate is chosen as low as possible irrespective of the channel state, and the processing gain is increased (decreased) as the channel becomes worse (better). The other observation made is that when DPSK modulation is employed, there exists an optimal combination of the code rate and the processing gain in maximizing the normalized throughput for each channel state. Based on these observations, we propose to adapt the processing gain and/or code rate according to the fading conditions in order to maximize the normalized throughput. We analyze the performance of the proposed scheme and compare it with the non-adaptive data transmission scheme. Our results show that the adaptive transmission scheme yields a significant performance improvement over the nonadaptive scheme, and increasing the adaptation level is more effective as the channel gets worse, but the 3-state adaptation seems to be practically optimum.

Resource Efficient Quality-Oriented Wireless Broadcasting of Adaptive Multimedia Content

The performance of multimedia stream delivery is influenced by encoding scheme, streaming solution and network conditions. This paper studies the performance of multimedia streaming when using the Quality-Oriented Adaptive Scheme (QOAS) over an IEEE 802.11b Wireless LAN and compares it to that achieved when using other solutions that do not consider end-user quality in their delivery process such as TFRC, LDA+, and non-adaptive schemes. The performance is assessed in terms of average end-user perceived quality, number of concurrent streaming sessions, loss rate, delay, jitter and total throughput when streaming MPEG-4 encoded content. Simulation results show that the QOAS out-performs these other streaming solutions in all aspects of network delivery. QOAS can support a greater number of concurrent streaming sessions at a higher average quality. In addition, for the same number of clients QOAS achieved a higher average end-user quality, as well as better network delivery streaming performance parameters

Adaptive MIMO Transmission for Exploiting the Capacity of Spatially Correlated Channels

We consider a novel low-complexity adaptive multiple-input multiple-output (MIMO) transmission technique. The approach is based on switching between low-complexity transmission schemes, including statistical beamforming, double space-time transmit diversity, and spatial multiplexing, depending on the changing channel statistics, as a practical means of approaching the spatially correlated MIMO channel capacity. We first derive new ergodic capacity expressions for each MIMO transmission scheme in spatially correlated channels. Based on these results, we demonstrate that adaptive switching between MIMO schemes yields significant capacity gains over fixed transmission schemes. We also derive accurate analytical approximations for the optimal signal-to-noise-ratio switching thresholds, which correspond to the crossing-points of the capacity curves. These thresholds are shown to vary, depending on the spatial correlation, and are used to identify key switching parameters. Finally, we propose a practical switching algorithm that is shown to yield significant spectral efficiency improvements over nonadaptive schemes for typical channel scenarios

Brewster-angled chirped mirrors for broadband pulse compression without dispersion oscillations

We use Brewster-angled chirped mirrors for dispersion compensation of a noncollinear optical parametric amplifier. This novel mirror design virtually eliminates spurious surface reflections and resultant dispersion ripple. The absence of compression artifacts is demonstrated by the generation of clean 5.6 fs pulses, with what is believed to be an unprecedented low ripple-induced satellite content for a nonadaptive scheme. In addition, the 270 THz spectral coverage allows generation of widely tunable visible pulses of 8 to 15 fs duration.

A New Hybrid ARQ-FEC Scheme For Wireless ATM Networks

Wired ATM (Asynchronous Transfer Mode) networks are designed taking into account an optical link in the physical layer. The main problem to implement a wireless ATM network is the fact that its radio link bit error rate is high and variable, demanding the use of an additional error control mechanism. The usual techniques for error control are ARQ (Automatic Repeat Request) and FEC (Forward Error Correction). ARQ works better than FEC if the channel bit error rate is low, and is worse if it is high, thus indicating that hybrid ARQ-FEC techniques can improve the radio link performance. A new hybrid ARQ-FEC scheme with multiple FEC states is proposed in this paper. The performance of the proposed scheme is compared with non-adaptive ARQ and FEC schemes, which have similar complexities, and with an ideal adaptive FEC scheme. It is shown that the proposed scheme works better than the non-adaptive schemes, and that the hybrid and the ideal adaptive FEC schemes have similar performances. Moreover, the hybrid scheme does not require an estimate of the bit error rate in the channel, leading to a less complex implementation.

Adaptive connection admission control for differentiated services access networks

In our earlier work, we have proposed some modifications for the bandwidth broker framework. With our modifications, it is possible to use measurement-based admission control in addition to the more traditional parameter-based admission control. Moreover, we have presented a new flexible admission control scheme that has proven to be very efficient in terms of bottleneck link utilization. Two problems, however, have arisen: the use of scheduling weights in admission control and bursty connection arrivals. In this paper, we present that the former one can be dealt with the use of adaptive scheduling weights, while the latter one can be fought with adaptive reservation limits. The proposed new algorithms are validated through simulations and their performance is compared against the nonadaptive basic scheme.

Adaptive Diagnosis in Distributed Systems

Real-time problem diagnosis in large distributed computer systems and networks is a challenging task that requires fast and accurate inferences from potentially huge data volumes. In this paper, we propose a cost-efficient, adaptive diagnostic technique called active probing. Probes are end-to-end test transactions that collect information about the performance of a distributed system. Active probing uses probabilistic reasoning techniques combined with information-theoretic approach, and allows a fast online inference about the current system state via active selection of only a small number of most-informative tests. We demonstrate empirically that the active probing scheme greatly reduces both the number of probes (from 60% to 75% in most of our real-life applications), and the time needed for localizing the problem when compared with nonadaptive (preplanned) probing schemes. We also provide some theoretical results on the complexity of probe selection, and the effect of "noisy" probes on the accuracy of diagnosis. Finally, we discuss how to model the system's dynamics using dynamic Bayesian networks (DBNs), and an efficient approximate approach called sequential multifault; empirical results demonstrate clear advantage of such approaches over "static" techniques that do not handle system's changes.

An adaptive scheme for fault-tolerant scheduling of soft real-time tasks in multiprocessor systems

The scheduling of real-time tasks with primary-backup-based fault-tolerant requirements has been an important problem for several years. Most of the known scheduling schemes are non-adaptive in nature meaning that they do not adapt to the dynamics of faults and task's parameters in the system. In this paper, we propose an adaptive fault-tolerant scheduling scheme that has a mechanism to control the overlap interval between the primary and backup versions of tasks such that the overall performance of the system is improved. The overlap interval is determined based on the observed fault rate and task's soft laxity. We also propose a new performance index, called SR index, that integrates schedulability ( S) and reliability ( R) into a single metric. To evaluate the proposed scheme, we have conducted analytical and simulation studies under different fault and deadline scenarios, and found that the proposed adaptive scheme adapts to system dynamics and offers better SR index than that of the non-adaptive schemes.

A Heterogeneous Built-In Self-Repair Approach Using System-Level Synthesis Flexibility

Summary and Conclusions -A novel methodology is proposed for designing fault-tolerant real-time multi-processor systems-on-a-chip to achieve optimal productivity. The methodology employs the heterogeneous built-in-self-repair (BISR) based on graceful degradation and yield enhancement techniques as an embedded optimization engine. The technique exploits the flexibility provided in task-level scheduling and algorithm selection steps. A hardware fault model is developed for modern super-scalar processors and multi-processors which enables an efficient treatment of the synthesis and compilation goals. For the first time, heterogeneous BISR is used at the task level. The key idea is to adapt scheduling and algorithm selection to the available nonfaulty resources. If there is a fault in memory, the algorithms that use less memory are selected and the scheduler exploits the other abundant resource, viz, the processors, more vigorously to compensate for the loss of part of memory. Similarly, a fault in a processor is backed up by memory. The synthesis approach minimizes the degradation in performance for single or multiple faults using simulated annealing-based algorithm selection, scheduling, and assignment algorithms. On the large set of examples this adaptive algorithm selection and scheduling technique has achieved important improvement of throughput compared to conventional nonadaptive schemes. The experimental results also indicate that important improvement in productivity can be achieved by using the extra throughput gained from the technique.

Adaptive bandwidth framework for provisioning connection-level QoS for next-generation wireless cellular networks

The next generation of wireless cellular networks is expected to support real-time multimedia services with different classes of traffic and diverse bandwidth requirements. Bandwidth is a scarce resource in wireless networking that needs to be carefully allocated amid competing connections with different quality of service (QoS) requirements. In this paper, an adaptive framework for supporting multiple classes of multimedia services with different QoS requirements in wireless cellular networks is proposed. The framework combines the following components: (1) a threshold-based bandwidth allocation policy that gives priority to handoff calls over new calls and prioritizes among different classes of handoff calls by assigning a threshold to each class; (2) an efficient threshold-type call admission control (CAC) algorithm; and (3) a bandwidth adaptation algorithm (BAA) that dynamically adjusts the bandwidth of ongoing multimedia calls to minimize the number of calls receiving lower bandwidth than they had requested. Numerical results show that the proposed adaptive multimedia framework outperforms existing non-adaptive schemes in terms of the handoff call dropping probability and effective utilization.