Performance of robust symbol‐timing and carrier‐frequency estimation for OFDM systems

In recent years, many maximum likelihood (ML) blind estimators have been proposed to estimate timing and frequency offsets for orthogonal frequency division multiplexing (OFDM) systems. However, the previously proposed ML blind estimators utilizing cyclic prefix do not fully characterize the random observation vector over the entire range of the timing offset and will significantly degrade the estimation performance. In this paper, we present a global ML blind estimator to compensate the estimation error. Moreover, we extend the global ML blind estimator by accumulating the ML function of the estimation parameters to achieve a better accuracy without increasing the hardware or computational complexity. The simulation results show that the proposed algorithm can significantly improve the estimation performance in both additional white Gaussian noise and ITU‐R M.1225 multipath channels. Copyright © 2008 John Wiley & Sons, Ltd.     

SD‐WLB: An SDN‐aided mechanism for web load balancing based on server statistics

Software‐defined networking (SDN) is a modern approach for current computer and data networks. The increase in the number of business websites has resulted in an exponential growth in web traffic. To cope with the increased demands, multiple web servers with a front‐end load balancer are widely used by organizations and businesses as a viable solution to improve the performance. In this paper, we propose a load‐balancing mechanism for SDN. Our approach allocates web requests to each server according to its response time and the traffic volume of the corresponding switch port. The centralized SDN controller periodically collects this information to maintain an up‐to‐date view of the load distribution among the servers, and incoming user requests are redirected to the most appropriate server. The simulation results confirm the superiority of our approach compared to several other techniques. Compared to LBBSRT, round robin, and random selection methods, our mechanism improves the average response time by 19.58%, 33.94%, and 57.41%, respectively. Furthermore, the average improvement of throughput in comparison with these algorithms is 16.52%, 29.72%, and 58.27%, respectively.     

Optimization‐based workload distribution in geographically distributed data centers: A survey

Energy efficiency is a contemporary and challenging issue in geographically distributed data centers. These data centers consume significantly high energy and cast a negative impact on the energy resources and environment. To minimize the energy cost and the environmental impacts, Internet service providers use different approaches such as geographical load balancing (GLB). GLB refers to the placement of data centers in diverse geolocations to exploit variations in electricity prices with the objective to minimize the total energy cost. GLB helps to minimize the overall energy cost, achieve quality of service, and maximize resource utilization in geo‐distributed data centers by employing optimal workload distribution and resource utilization in the real time. In this paper, we summarize various optimization‐based workload distribution strategies and optimization techniques proposed in recent research works based on commonly used optimization factors such as workload type, load balancer, availability of renewable energy, energy storage, and data center server specification in geographically distributed data centers. The survey presents a systemized and a novel taxonomy of workload distribution in data centers. Moreover, we also debate various challenges and open research issues along with their possible solutions.     

On parameter estimation of a simple real‐time flow aggregation model

There exists a clear need for a comprehensive framework for accurately analysing and realistically modelling the key traffic statistics that determine network performance. Recently, a novel traffic model, sinusoid with uniform noise (SUN), has been proposed, which outperforms other models in that it can simultaneously achieve tractability, parsimony, accuracy (in predicting network performance), and efficiency (in real‐time capability). In this paper, we design, evaluate and compare several estimation approaches, including variance‐based estimation (Var), minimum mean‐square‐error‐based estimation (MMSE), MMSE with the constraint of variance (Var+MMSE), MMSE of autocorrelation function with the constraint of variance (Var+AutoCor+MMSE), and variance of secondary demand‐based estimation (Secondary Variance), to determining the key parameters in the SUN model. Integrated with the SUN model, all the proposed methods are able to capture the basic behaviour of the aggregation reservation system and closely approximate the system performance. In addition, we find that: (1) the Var is very simple to operate and provides both upper and lower performance bounds. It can be integrated into other methods to provide very accurate approximation to the aggregation's performance and thus obtain an accurate solution; (2) Var+AutoCor+MMSE is superior to other proposed methods in the accuracy to determine system performance; and (3) Var+MMSE and Var+AutoCor+MMSE differ from the other three methods in that both adopt an experimental analysis method, which helps to improve the prediction accuracy while reducing computation complexity. Copyright © 2005 John Wiley & Sons, Ltd.     

MC‐CDMA MIMO systems with quasi‐orthogonal space–time block codes: Channel estimation and multiuser detection

This paper investigates blind channel estimation and multiuser detection for quasi‐synchronous multi‐carrier code‐division multiple‐access (MC‐CDMA) multiple‐input multiple‐output (MIMO) systems with quasi‐orthogonal space–time block codes (QO‐STBC). Subspace‐based blind channel estimation is proposed by considering a QO‐STBC scheme that involves four transmit antennas and multiple receive antennas. Based on the first‐order perturbation theory, the mean square error of the channel estimation is derived. With the estimated channel coefficients, we employ minimum output energy and eigenspace receivers for symbol detection. Using the QO‐STBC coding property, the weight analyses are performed to reduce the computational complexity of the system. In addition, the forward–backward averaging technique is presented to enhance the performance of multiuser detection. Numerical simulations are given to demonstrate the superiority of the proposed channel estimation methods and symbol detection techniques. Copyright © 2011 John Wiley & Sons, Ltd.     

Two‐pilot channel estimation scheme for amplify‐and‐forward relay networks

In amplify‐and‐forward relay networks, the equivalent channel to the destination node is not independent of equivalent noise and the equivalent noise does not follow a Gaussian distribution. Therefore, it is difficult to directly estimate the equivalent channel based on traditional optimal rules. In this paper, we propose a two‐pilot estimation (TPE) scheme that decomposes a non‐Gaussian noise channel estimation problem into two channel estimation problems in Gaussian noise. In TPE scheme, the relay‐destination channel is first estimated by one pilot and the other pilot is used to estimate the equivalent channel with the aid of the estimated relay‐destination channel. Simulation results show that the TPE scheme can achieve less estimation error and larger system throughput than other existing channel estimators in slow fading case. Copyright © 2012 John Wiley & Sons, Ltd.     

Multiuser receiver scheme for full‐rate space–time coded CDMA system with imperfect estimation

By introducing a full‐rate space–time coding (STC) scheme, a synchronous CDMA (code division multiple access) system with full‐rate STC is given, and the corresponding uplink performance is investigated in Rayleigh fading channel with imperfect estimation. Considering that existing STC‐CDMA system has high decoding complexity, low‐complexity multiuser receiver schemes are developed for perfect and imperfect estimations, respectively. The schemes can make full use of the complex orthogonality of STC to reduce the high decoding complexity of the existing scheme, and have linear decoding complexity compared with the existing scheme with exponential decoding complexity. Moreover, the proposed schemes can achieve almost the same performance as the existing scheme. Compared with full‐diversity STC‐CDMA, the given full‐rate STC‐CDMA can achieve full data rate, low complexity, and partial diversity, and form efficient spatial interleaving. Thus, the concatenation of channel coding can effectively compensate for the performance loss due to partial diversity. Simulation results show that the full‐rate STC‐CDMA has lower bit error rate (BER) than full‐diversity STC‐CDMA systems under the same system throughput and concatenation of channel code. Moreover, the system BER with imperfect estimation are worse than that with perfect estimation due to the estimation error, which implies that the developed multiuser receiver schemes are valid and reasonable. Copyright © 2010 John Wiley & Sons, Ltd.     

Hopfield neural‐network‐based dynamic resource allocation scheme for non‐real‐time traffic in wireless networks

Dynamic resource allocation (DRA) plays a fundamental role in current and future wireless networks, including 3G systems. In this paper, a scheduling DRA scheme for non‐real‐time (NRT) packet services in wireless system is proposed based on the use of Hopfield neural networks (HNN). The scheme exploits the fast response time of HNN for solving NP optimization problems and has been particularized for the downlink transmission in a UMTS system, although it could be easily extended to any other radio access technology. The new DRA scheme follows a delay‐centric approach, since it maximizes the overall system resource utilization while minimizing the packet delay. Simulation results confirm that the proposed HNN‐based DRA scheme is effective in supporting different types of NRT services, while achieving efficient utilization of radio resources. Copyright © 2008 John Wiley & Sons, Ltd.     

Probabilistic response‐time analysis for real‐time systems in body area sensor networks

Advances in real‐time system and wireless communication have led to the deployment of body area sensor networks (BASNs) for effective real‐time healthcare applications. Real‐time systems in BASNs tend increasingly to be probabilistic and mixed critical to meet stringent requirements on space, weight, and power consumption. Response‐time analysis is an important and challenging task for BASNs to provide some critical services. In this paper, we propose a request‐based compositional probabilistic response‐time analysis framework for probabilistic real‐time task models with fixed‐priority preemptive scheduling in BASNs. In this method, each probabilistic real‐time task is abstracted as a probabilistic request function. Rough response‐time distribution is computed first based on the cumulative request distribution and then exact response‐time distribution is obtained by refinement based on the request increase distribution. Our strategy can effectively improve performance by reducing repetitive computational overhead for the probabilistic response‐time analysis of all tasks in the system. Our evaluation demonstrates that our proposed method significantly outperforms the existing probabilistic response‐time analysis algorithm in terms of analysis duration. Copyright © 2015 John Wiley & Sons, Ltd.     

Channel estimation joint DOAs and time delay correlation in TD‐SCDMA mobile radio systems

An improved channel estimation technique based on the Steiner low‐cost channel estimator is proposed, which is widely used in TD‐SCDMA (Time Division‐Synchronous Code Division Multiple Access) cellular mobile radio systems. TD‐SCDMA is also known as third‐generation mobile systems where adaptive antennas are employed. As additive noise has a great adverse effect on the performance of the Steiner estimator, the proposed method employs time‐correlated post‐processing with a threshold filter to reduce channel noise and compensate channel variations. Furthermore, channel estimation combining direction‐of‐arrivals (DOAs) is performed, which can reduce channel interferences without adding computational complexity, for the information of DOAs has been obtained by the inherent adaptive antenna system. The performance of the improved channel estimator is compared with conventional channel estimation approaches, and numerical results show that the new approach can lead to considerable performance enhancement even in high‐speed vehicle propagation environments. Copyright © 2008 John Wiley & Sons, Ltd.