Online ISSN
1751-8636
Print ISSN
1751-8628
IET Communications
Volume 6, Issue 18, 18 December 2012
Volumes & issues:
Volume 6, Issue 18
18 December 2012
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- Author(s): Z. Talepour ; J. Ahmadi-Shokouh ; S. Tavakoli
- Source: IET Communications, Volume 6, Issue 18, p. 3059 –3064
- DOI: 10.1049/iet-com.2012.0272
- Type: Article
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In this study, the authors consider a transmitter location finding problem in a wireless network equipped with RAKE receivers. In these types of receivers, fading is mitigated in the wireless communication channel. This fading is due to multiple versions of the transmitted signal at a spread of arrival times. In the RAKE receiver, a certain number of them are needed – called strongest – to have received signal strength above a threshold. In the optimum location finding problem, the number of bad receiving points determined based on a proposed error function is minimised. Two different criteria, which are defined through the RAKE receiver architecture, form this error function. Thus, a multi-objective optimisation problem is herein solved in order to solve transmitter location finding problem. The proposed optimisation method contains a jointly designed ray tracing engine (RTE) and genetic algorithm (GA). The algorithm is applied on a sample environment, which is fully simulated with RTE. The GA, which is integrated to RTE, determines optimum location(s) of transmitters. The results show that the proposed method perfectly finds the best locations of the minimum number of transmitters. - Author(s): M. Sayed Hassan and K. Amis
- Source: IET Communications, Volume 6, Issue 18, p. 3065 –3074
- DOI: 10.1049/iet-com.2012.0424
- Type: Article
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Non-orthogonal space-time block (STB) code structures used to be optimised considering a maximum-likelihood detection, but depending on the modulation order and/or the antenna number, the prohibitive complexity of such a receiver makes it infeasible in practice. Suboptimal low-complexity receiver structures like linear detectors can be applied instead, yielding degradation of performance compared with the predictions. When a forward error correction (FEC) code is used upstream of the STB code, an iterative receiver consisting of a FEC decoder and an interference canceller (IC) co-operating according to the turbo equalisation principle, can achieve near-optimal performance. This study aims to define the construction of full-rate full-diversity linear dispersion codes with reduced peak-to-average power ratio (PAPR), taking into account the serial concatenation with a FEC at the transmitter and a minimum mean square error (MMSE) turbo equaliser at the receiver. Optimisation criteria are mutual information maximisation, symbol error rate minimisation at the MMSE–IC output, full-diversity thanks to the threaded algebraic space time concept and PAPR minimisation. Explicit constructions are given and the resulting code efficiency is analysed through comparison with equivalent perfect STB codes. - Author(s): G. Wang ; K. Shao ; L. Zhuang
- Source: IET Communications, Volume 6, Issue 18, p. 3075 –3083
- DOI: 10.1049/iet-com.2012.0041
- Type: Article
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In the current communication standards, like WiMAX and LTE, the modulation system has usually fixed symbol block length or fixed subcarrier number. In this study, the authors introduce a new concept, namely time-varying symbol block or time-varying subcarrier number into the modulation systems to improve the system performance. The authors call the new modulation system time-varying orthogonal frequency-division multiplexing, time-varying orthogonal frequency-division multiple access for multicarrier modulation and time-varying single-carrier frequency-division multiple access for single-carrier modulation. Here, peak-to-average power ratio (PAPR) is used as a criteria to change the symbol block length timely. The algorithm for determination of the symbol block length is presented. The simulation results show that the time-varying modulation schemes can clearly reduce the PAPR values for both multicarrier and single carrier modulation systems. - Author(s): B. Zhu ; J. Ge ; J. Li ; C. Sun
- Source: IET Communications, Volume 6, Issue 18, p. 3084 –3090
- DOI: 10.1049/iet-com.2012.0467
- Type: Article
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An iterative interference alignment (IA) algorithm for the multi-user multi-input multi-output interference channel is proposed, which optimises on the Grassmann manifold to improve the performance of conventional interference subspace (ISS) alignment algorithm without the assumption of channel reciprocity. The proposed algorithm combines the extreme eigenvalues method and the modified steepest descent method on the Grassmann manifold to minimise the distances not only between the ISS and the subspace spanned by interference, but also between the desired signal subspace and the subspace spanned by useful signal. Utilising the subspace optimisation above, both the interference and useful signal are aligned to their respective subspaces. Numerical results show that the proposed algorithm can significantly improve the sum rate of interference channel. Moreover, by properly choosing the attenuation factor of step size, the proposed algorithm can achieve an effective tradeoff between sum rate performance and convergence speed, which gives the IA scheme more design flexibility. - Author(s): B. Luo ; H. Yu ; X. Zhang ; Z. Shen ; Q. Li
- Source: IET Communications, Volume 6, Issue 18, p. 3091 –3097
- DOI: 10.1049/iet-com.2012.0141
- Type: Article
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In typical signal combining scenarios, the combining weights are estimated using the criterion of maximum average signal-to-noise ratio (SNR) or maximum combined output power (COP). Eigen-based algorithms are very important and popular in signal combining. The conventional SNR EIGEN or COP EIGEN may not necessarily be effective in terms of performance or system complexity. The main contribution of this study is the introduction of the combined signal autocorrelation coefficient as a newer objective function to signal combining. The corresponding eigen-based combining algorithm AC EIGEN and its modified algorithm MAC EIGEN are also derived. Proposed algorithms have the same simple system structure as the COP EIGEN, which can successfully avoid estimating the noise correlation matrix. Simulation results indicate that the AC EIGEN and the MAC EIGEN have good combining performance for signals with white Gaussian noise when the SNR of the signals is low. Considering the system complexity of the SNR EIGEN, and the COP EIGEN being biased for non-uniform noise variance signals, the proposed algorithms are attractive. - Author(s): B.M. Mthethwa and H. Xu
- Source: IET Communications, Volume 6, Issue 18, p. 3098 –3108
- DOI: 10.1049/iet-com.2012.0396
- Type: Article
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Spatial modulation (SM) is a low complexity, highly spectral efficient multiple-input–multiple-output scheme that has been proposed in the literature. The authors apply adaptive modulation to conventional SM in order to maximise the average throughput of the scheme. For this to be possible, the equivalent received signal-to-noise ratio (SNR) needs to be defined and is done so via two proposed approaches: using the first-order statistics SNR and using the average statistics SNR. Average theoretical bit-error-rate (BER) bounds are derived for both of these SNR approaches. Also, adaptive M-ary quadrature amplitude spatial modulation switching levels are determined to maximise the throughput while meeting the average target BER. The Monte Carlo simulation results successfully validate the derived theoretical BER bounds and also prove that the average throughput is improved in comparison to conventional SM. The two proposed definitions for the equivalent received SNR are confirmed to yield comparable BER and throughput performances via simulations, implying that the equivalent received SNR can be defined using either approach. - Author(s): J. Yang ; X. Rui ; X. Cao
- Source: IET Communications, Volume 6, Issue 18, p. 3109 –3113
- DOI: 10.1049/iet-com.2012.0273
- Type: Article
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There are two fundamental channel models in decode-and-forward (DF) multihop relaying system: one is DF multihop channel and the other is DF multihop diversity channel. The latter outperforms the former at the cost of computational and hardware complexity at each relay. In this study, the authors consider a trade-off of the above two channel models and propose a new channel model, which is DF multihop channel with direct link. The new channel model can exploit partial spatial diversity without any extra request for the receiver of relays. The authors focus on the optimal power allocation problem of their proposed system. The authors first derive the end-to-end outage probability, and then they formulate and evaluate the optimisation problem by minimising the outage probability under the total power constraint. Numerical results demonstrate that their proposed system can improve system performance compared with fundamental multihop relaying system. In addition, their proposed power allocation scheme can effectively enhance the system performance compared with uniform power allocation scheme, especially if the number of relays is large. - Author(s): X. Li ; L.L. Zhou ; S. Jin ; X.Q. Gao
- Source: IET Communications, Volume 6, Issue 18, p. 3114 –3121
- DOI: 10.1049/iet-com.2012.0433
- Type: Article
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Multi-user multiple antenna systems have attracted much attention because of large spectral efficiency. However, receiver and transmitter channel state information (CSI) is generally required, especially for the downlink channel. In this study, the authors investigate the ergodic sum rate and present low complexity adaptive transmission scheme for multiple-input single-output downlink multi-user systems with statistical CSI at the base station (BS). The authors derive an approximation of the ergodic sum rate, and the constraint of each user's statistical CSI under which the approximation of the ergodic sum rate is maximised. Then, statistical beamforming space division multiple access transmission is derived through maximising the approximation of the ergodic sum rate, and new adaptive transmission schemes are proposed. The proposed algorithms are shown to perform well and require the BS only to know the statistical CSI of each user. - Author(s): M.M.H. El Ayadi and M.H. Ismail
- Source: IET Communications, Volume 6, Issue 18, p. 3122 –3130
- DOI: 10.1049/iet-com.2012.0271
- Type: Article
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The sum and harmonic mean of random variables (RVs) appear frequently in performance evaluation studies of wireless communications systems. In particular, the sum appears in the performance evaluation of maximal ratio combining (MRC) and equal gain combining (EGC) diversity receivers whereas the harmonic mean is encountered in performance evaluation studies of cooperative diversity networks with non-regenerative relays. In this study, the authors propose highly accurate finite-series approximations for the cumulative distribution function (CDF) of the sum and harmonic mean of two α−μ distributed RVs. The proposed approximations do not require neither a look-up table nor solving complicated transcendental equations, as is typically the case in the literature. The results reveal that the proposed approximations are very accurate over the typical range of interest when compared with the exact CDFs computed using numerical integration methods. - Author(s): X. Xu ; J. Wu ; S. Ren ; L. Song ; H. Xiang
- Source: IET Communications, Volume 6, Issue 18, p. 3131 –3139
- DOI: 10.1049/iet-com.2012.0418
- Type: Article
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In this study, the superimposed training strategy is introduced into orthogonal frequency division multiplexing-modulated amplify-and-forward two-way relay network (TWRN) to perform two-hop transmission-compatible individual channel estimation. Through the superposition of an additional training vector at the relay under power allocation, the separated source–relay channel information can be directly obtained at the destination and then used to estimate the channels. The closed-form Bayesian Cramér-Rao lower bound (CRLB) is derived for the estimation of block-fading frequency-selective channels with random channel parameters, and orthogonal training vectors from the two source nodes are required to keep the Bayesian CRLB simple because of the self-interference in the TWRN. A set of optimal training vectors designed from the Bayesian CRLB are applied in an iterative linear minimum mean-square-error channel estimation algorithm, and the mean-square-error performance is provided to verify the Bayesian CRLB results. - Author(s): W. Xu ; B. Zheng ; J. Zhang
- Source: IET Communications, Volume 6, Issue 18, p. 3140 –3149
- DOI: 10.1049/iet-com.2011.0690
- Type: Article
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Integer least square problem is widely used in wireless communications, cryptography and some other fields. In this study, the authors propose a radius bisection algorithm with restart strategy to solve the ILS problem. Compared with the original sphere-decoding method, the algorithm can solve the ILS problem with higher speed and lower complexity. Also, users can specify a stop criterion to control the accuracy and complexity of the algorithm. Finally, some simulated experiments show the efficiency and effectiveness of the proposed algorithm. - Author(s): S.J. Nawaz ; K.I. Ahmed ; M.N. Patwary ; N.M. Khan
- Source: IET Communications, Volume 6, Issue 18, p. 3150 –3156
- DOI: 10.1049/iet-com.2012.0162
- Type: Article
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In a number of wireless communication applications, the impulse response of multipath communication channels has sparse nature. In this study, physical model for various propagation environments exhibiting sparse channel structure is considered. A superimposed (SI) training-based compressed channel sensing (SI-CCS) technique is proposed for such sparse multipath channels. A non-random periodic pilot sequence is SI over the information sequence at the transmitter, which avoids the use of dedicated time slots for training sequence. At the receiver, first-order statistics and the theory of compressed sensing is applied to estimate the wireless communication channels with sparse impulse response. A simulation analysis is presented to demonstrate the effectiveness of the proposed-channel estimation technique, where mean-square error and bit-error rate are used as the performance measures. Exploiting the proposed SI-CCS technique, the simulation results along with the observations are presented, which illustrate the effect of various channel parameters on the performance of the proposed technique. Furthermore, obtained simulation results for the proposed SI-CCS technique along with its comparison with other techniques in literature are also presented. It is established that for the cases of sparse multipath channels, the proposed SI-CCS technique can potentially achieve significant improvement in the performance of channel estimator over the existing estimation techniques of such sparse channels. - Author(s): D. Xie and Y. Li
- Source: IET Communications, Volume 6, Issue 18, p. 3157 –3164
- DOI: 10.1049/iet-com.2011.0533
- Type: Article
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A simplified soft decoding algorithm for the (23, 12, 7) Golay code that can correct up to six errors is proposed in this study. The emblematic probability value of this algorithm derived from Reed is shown to be the same as the one given by Chase, if a joint estimate of the noise power and the received bit amplitude are carried out at the output of the matched filter in a Costas-loop receiver. Simulation results show that the coding gain obtained by the simplified algorithm is nearly the same as that achieved by Chase's algorithm. Based on the simplified algorithm, this study investigates an efficient hardware implementation on field programmer gate array platform, and presents a detailed architecture of the soft decoder. Experimental result indicates that the proposed algorithm uses less hardware complexity and has high-throughput rate, therefore it is naturally suitable for very large scale integration (VLSI) implementation. - Author(s): F.K. Gong ; P. Ye ; Y. Wang ; N. Zhang
- Source: IET Communications, Volume 6, Issue 18, p. 3165 –3175
- DOI: 10.1049/iet-com.2012.0215
- Type: Article
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Double Nakagami-m fading model can be used to provide a realistic description of the mobile-to-mobile (M2M) channel. The moment generating function (MGF)-based approach is used to derive the symbol error probability (SEP) expressions for the multiple-mobile-relay-based M2M system. Under the consideration of better performance and lower complexity, both decode-and-forward (DF) and amplify-and-forward (AF) protocols are addressed in this study. For adaptive DF (ADF) relaying, the asymptotic SEP at high signal-to-noise ratio regime in addition to the exact SEP formulations are derived. Furthermore, the impacts of channel estimation error for the insight of non-ideal channel estimation are analysed. For fixed-gain AF (FAF) relaying, the authors present approximate SEP and asymptotic SEP to indicate the cooperative gain. For L mobile relays and under the assumption of independent and identically distributed (i.i.d) source–relay channels and i.i.d relay–destination channels, it is shown in this paper that asymptotic diversity orders of L×min(mRD,1, mRD,2)+min(mSD,1, mSD,2) and L×min(mSR,1, mSR,2, mRD,1, mRD,2)+min(mSD,1, mSD,2) can be achieved for ADF-M2M and FAF-M2M schemes, respectively. Simulations are performed to verify the analytical results. - Author(s): J.A. Martín-González ; O. González ; E. Poves ; F.J. López-Hernández ; R. Pérez-Jiménez
- Source: IET Communications, Volume 6, Issue 18, p. 3176 –3188
- DOI: 10.1049/iet-com.2012.0305
- Type: Article
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In this study, the authors present a technique for code acquisition in optical code-division multiple-access systems using the recently introduced random optical codes. In these systems, the communication is divided in two parts: a synchronisation process and the data transmission. The main target of the study is to describe and analyse the new algorithm of synchronisation using Markov processes. Once described the code acquisition technique and established an estimation for the probability of false alarm (FA) of the proposed scheme, two different proposals for the optimisation of the code parameters are described. They are based on two different estimators for the probability of FA. The first one considers the expected value for the probability of FA. The second one is very much restrictive. It guarantees that the probability of FA is in a confidence interval. It takes the upper bound of the confidence interval as estimator for the probability of FA. Although the second one presents worse acquisition time, the authors consider that the gain provided by the first method is not sufficient enough to assume its loss in the reliability. Thus, the authors propose to guarantee the probability of FA in a confidence interval. A compromise between reliability and acquisition time is obtained with this second method. - Author(s): J. Yan and L. Wu
- Source: IET Communications, Volume 6, Issue 18, p. 3189 –3195
- DOI: 10.1049/iet-com.2011.0951
- Type: Article
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A base station (BS) identification algorithm which does not modify the transmitter hardware and digital terrestrial television broadcasting signal framework is proposed for single-frequency networks positioning system. Similar to the outlier detection in multi-object tracking environments, the BS identification is formulated as a data validation problem which is solved with gate construction. Compared with traditional gate algorithm, an additional mode probability parameter is introduced to describe the wireless channel condition and overcome its drawback in non-stationary wireless channel environments by the interacting multiple model approach. In the proposed algorithm, two parallel innovation statistical distribution deduction modes with line-of-sight and non-line-of-sight condition are employed to estimate the corresponding parameters, respectively. Then a combination scheme is utilised to mix the two estimated statistical parameters by the predicted mode probabilities and obtains the final innovation distribution. At last, gate parameter is calculated like traditional gate algorithm and the BS identification is achieved. Simulation results demonstrate its robustness and high performance in different scenarios. - Author(s): H.-D. Han and Z. Ding
- Source: IET Communications, Volume 6, Issue 18, p. 3196 –3203
- DOI: 10.1049/iet-com.2011.0764
- Type: Article
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In the literature, there exists a number of blind signal recovery algorithms that are implemented as stochastic gradient descent (SGD)-based adaptive schemes. SGD typically has low complexity at the expense of slower convergence. On the other hand, packet-based data transmission in many practical digital communication systems makes it attractive to develop steepest descent (SD) implementation in order to speed-up convergence. This work aims at developing SD implementation of several well-known blind signal recovery algorithms for multi-channel equalisation and source separation. The authors SD formulation is more amenable to additional parametric and signal subspace constraint for faster convergence and superior performance. - Author(s): W.-C. Pao and Y.-F. Chen
- Source: IET Communications, Volume 6, Issue 18, p. 3204 –3212
- DOI: 10.1049/iet-com.2011.0844
- Type: Article
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The capacity maximisation problem of the secondary user subject to an interference constraint in orthogonal frequency division multiplexing-based cognitive radio systems is studied in this paper. A novel constant interference strategy to allocate power to subcarriers is derived, where all selected subcarriers are subject to the same interference constraint. It means all subcarriers have the same interference power. This strategy ensures the original interference constraint satisfied. The capacity loss of the proposed methods compared with the optimal solution is also analysed. An upper bound of the capacity loss is derived. Its value can determine the potential benefit of the proposed methods even if the optimal solution is not obtained. Therefore an advanced strategy to select subcarriers to allocate power becomes important, which affects the performance of the proposed methods and the upper bound. By using a proposed indicator, two novel power allocation methods were presented with a lower complexity to select subcarriers for allocating power, which outperforms the existing methods. Performances of the proposed methods are very near that of the optimal solution. - Author(s): S. Tayyaba ; M.W. Ashraf ; N. Afzulpurkar
- Source: IET Communications, Volume 6, Issue 18, p. 3213 –3221
- DOI: 10.1049/iet-com.2011.0176
- Type: Article
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Here the authors present the new design of blood filtration system for patients with kidney diseases. The proposed system consists of electronic module, drug delivery part, blood extraction and blood insertion part, blood filtration part, flow sensors and blood pressure sensor. Electronic module provides necessary functionalities and control to other components of system. Using inductively coupled plasma etching technology hollow silicon microneedles have been developed for drug delivery part. Nano porous aluminium membrane has been fabricated for blood filtration part. Ultra-sharp tip polymeric dual radii microneedles have been proposed for blood extraction and insertion part. Using ANSYS, strength modelling, microfluidic static and multifield analyses have been conducted. Water, ethanol and blood have been used as working fluid in microfluidic analysis to foresee the flow rate and viscosity effect through microneedles. Fluidic analysis shows that the proposed design is suitable for blood transport because two different lumens radii in microneedles are useful to avoid the clogging effect because of pressure difference in the lumen regions. - Author(s): M. Abdelkader ; M. Hamdi ; N. Boudriga
- Source: IET Communications, Volume 6, Issue 18, p. 3222 –3230
- DOI: 10.1049/iet-com.2011.0303
- Type: Article
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The proliferation of fourth generation (4G) networks has motivated the development of new services characterised by ubiquity and convergence. This means that the end-user can access such services from everywhere through the use of multiple networking infrastructures. Despite the benefits resulting from such services, they are intrinsically vulnerable to many spoofing attacks. Thus, a user needs to be identified and authenticated to different serving networks and service providers. The definition of different identities for the same user would be hardly manageable since it would introduce identity confusion and heavy management procedures, especially in the overlapping zones. This study proposes a unique identifer assignment and management techniques in a heterogeneous 4G environment. In this study, the authors introduce a new syntax for the temporal mobile subscriber identity and develop the associated secure identity management process. The proposed scheme, the so-called advanced identity management guarantees mutual authentication, privacy and tracking avoidance, which are of primary importance in 4G networks. - Author(s): S. Al-Ahmadi
- Source: IET Communications, Volume 6, Issue 18, p. 3231 –3237
- DOI: 10.1049/iet-com.2012.0334
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The performance analysis of different transmission schemes in emerging wireless communication systems such as outdoor distributed antenna architectures and relay networks requires the adoption of joint multipath fading and shadowing channel models, since the geographically distributed ports experience different small-scale and large-scale fading conditions. In this study, extreme value theory is utilised to quantify the ergodic capacity of multiuser diversity (opportunistic scheduling) over shadowed Nakagami (gamma–gamma) fading channels. The distribution of the maximum extreme for a sequence of independent and identically distributed gamma–gamma random variables is shown to belong to the domain of attraction of the Gumbel distribution and subsequently the effect of independent shadowing on the ergodic capacity of opportunistic scheduling for large number of users is revealed. - Author(s): T.-W. Kim and H.-C. Kim
- Source: IET Communications, Volume 6, Issue 18, p. 3238 –3247
- DOI: 10.1049/iet-com.2011.0086
- Type: Article
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Vital signs such as respiration and pulse and electrocardiography are crucial for monitoring disease and promoting health in the age of ubiquitous cloud computing. However, systems and devices that sense, process and analyse vital signs suffer from a lack of interoperability caused by differences in the platforms, devices and data formats used. Consequently, a particular vendor can provide a limited number of services, but users are not able to access more shared services. To counter these problems, this study proposes a service-oriented architecture for healthcare systems utilising vital signs. The proposed structure differs from the one used to handle business logics in general, because vital signs data are distinct from the types of data used in other enterprises. In this study, these data are expressed as the Health Level Seven standard schema, and the structure uses Object Constraint Language (OCL), a platform-independent specification language, to access the vital signs data and evaluate the state of health. In particular, the use of OCL enables a fast response to changes in service content and reduces maintenance costs. - Author(s): M.W. Ashraf ; S. Tayyaba ; A. Nisar ; N. Afzulpurkar
- Source: IET Communications, Volume 6, Issue 18, p. 3248 –3256
- DOI: 10.1049/iet-com.2011.0177
- Type: Article
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This study presents the fabrication and analysis of silicon hollow microneedles and polymeric piezoelectric valveless micropump for microelectromechanical (MEMS)-based transdermal drug-delivery (TDD) system. The proposed TDD system consists of integrated control electronics and MEMS devices such as micropump, microneedles, blood pressure sensor and fluid flow sensor. Microneedles and micropump are the most essential and critical components of the proposed TDD system. Mechanical strength of microneedles has been investigated in structural analysis. Inductively coupled plasma technology has been used to fabricate high aspect ratio silicon hollow microneedles. The numerical analysis of micropump has been done by building three-dimensional electro-fluid–solid model. The experimental performance of fabricated polymeric piezoelectric valveless micropump with different pump chamber diameters has been characterised in terms of actuator deflection and flow rate at different operational parameters. - Author(s): M. Hayat and A. Khan
- Source: IET Communications, Volume 6, Issue 18, p. 3257 –3264
- DOI: 10.1049/iet-com.2011.0170
- Type: Article
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Membrane proteins are fundamental elements of a cell that play essential roles nearly in all the cellular processes. Prediction of membrane protein types using biological experiments are often complicated and time consuming. Therefore it is highly desirable to develop a robust, reliable and high-throughput silico method to predict membrane protein types. In this study, the authors have used two feature extraction strategies known as dipeptide and pseudo amino acid (PseAA) compositions for classification of membrane proteins types. In addition, a composite model is also developed by concatenating dipeptide and PseAA composition based features. Further, two feature selection methods such as neighbourhood preserving embedding and locally linear embedding (LLE) are applied to reduce the dimensionality of the composite model. The performance of these feature extraction strategies is evaluated using four different classifiers: K-nearest neighbour, probabilistic neural network (PNN), support vector machine (SVM) and grey incidence degree. The highest success rates have been observed using the LLE-based reduced features. SVM has yielded the best accuracy of 88.2% in case of jackknife test. Although in case of independent dataset test, PNN has obtained the highest accuracy of 98.4%. Performance measures other than accuracy are also used such as ‘Mathew correlation coefficient’, sensitivity and precision. The authors simulated results show that the composite model has significantly discriminated the types of membrane protein and might be useful for future research and drug discovery. - Author(s): S. Ansari ; I. Shafi ; J. Ahmad ; S. Ismail Shah
- Source: IET Communications, Volume 6, Issue 18, p. 3265 –3273
- DOI: 10.1049/iet-com.2011.0186
- Type: Article
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A neural network-based method is presented for the diagnosis and classification of patients infected with hepatotropic viral disease. The non-invasive approach makes use of real-time pathological data in form of liver function tests and specific virological markers during training. The unknown patients, not included in the training set, are then processed through the trained neural network model. Experimental results demonstrate that the proposed method is able to effectively diagnose the disease and classifies its stage to be acute, chronic or cirrhosis. In addition, performance analysis is carried out for various supervised and unsupervised neural network models with optimal topologies. The topological architectures are chosen after experimenting with various training algorithms using diverse parameters such as different activation functions between layers, number of hidden layers, and number of neurons. It is concluded that the performance of the multilayered supervised feedforward neural network is the most accurate even with small data set. Whereas, the unsupervised Kohonen's self-organising maps do not perform well for the subject task under similar conditions. - Author(s): J. Pan ; S. Li ; Z. Xu
- Source: IET Communications, Volume 6, Issue 18, p. 3274 –3280
- DOI: 10.1049/iet-com.2011.0097
- Type: Article
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Recently, with the help of remote continuous healthcare monitoring technique, elderly people with chronic medical conditions can receive therapeutic service at home or at local community without going to hospitals. Wireless sensor networks promise to revolutionise the healthcare model by allowing inexpensive, non-invasive, continuous and ambulatory healthcare monitoring devices with almost real-time updates of medical records via the Intranet/Internet. The medical data of an individual is very personal, sensitive and should be kept in a reliable and authorised entity. However, the vital personal signals transmitting in the networks cannot be prohibited to be eavesdropped during the wireless communications. Worse still, the adversary could even actively modify, inject or spoof the private vital medical data. To address the issues of system security, a hybrid key management based on elliptic curve cryptography is proposed to protect sensitive data in these stringent resource-constrained devices. In order to protect data, two modified Feistel algorithms are introduced and compared with data encryption standard (DES). At the same time, a healthcare monitoring prototype has been implemented for testing the security mechanisms by using blood oxygen level (SpO2) physiological sensor module and MICAz nodes. - Author(s): S.Z. Erdogan and T.T. Bilgin
- Source: IET Communications, Volume 6, Issue 18, p. 3281 –3287
- DOI: 10.1049/iet-com.2011.0228
- Type: Article
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Fall detection technology is critical for the elderly people. In order to avoid the need of full time care giving service, the actual trend is to encourage elderly to stay living autonomously in their homes as long as possible. Reliable fall detection methods can enhance life safety of the elderly and boost their confidence by immediately alerting fall cases to caregivers. This study presents an algorithm of fall detection, which detects fall events by using data-mining approach. The authors' proposed method performs detection in two steps. First, it collects the wireless sensor network (WSN) data in stream format from sensor devices. Second, it uses k-nearest neighbour algorithm, that is, well-known lazy learning algorithm to detect fall occurrences. It detects falls by identifying the fall patterns in the data stream. Experiments show that the proposed method has promising results on WSN data stream in detecting falls. - Author(s): J.Y. Chun ; D.H. Lee ; I.R. Jeong
- Source: IET Communications, Volume 6, Issue 18, p. 3288 –3293
- DOI: 10.1049/iet-com.2011.0108
- Type: Article
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Hospitals have to use a large amount of medical data from individuals while protecting their privacy to execute medical data mining. It is important to find ‘rare’ cases among medical data of individuals in many healthcare applications. Therefore hospitals need privacy-preserving mining techniques to find rare cases among medical data of individuals. However, previous privacy-preserving data-mining techniques cannot be used to find rare cases. In this study, they suggest a privacy-preserving ‘range set union’ protocol that can be used to find rare cases in the private medical datasets of individuals. - Author(s): N. Xiong ; W. Han ; A. Vandenberg
- Source: IET Communications, Volume 6, Issue 18, p. 3294 –3300
- DOI: 10.1049/iet-com.2011.0293
- Type: Article
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The authors are particularly aware that green cloud computing (GCC) is a broad range and a hot field. The distinction between ‘consumer of’ and ‘provider of’ cloud-based energy resources may very important in creating a world-wide ecosystem of GCC. A user simply submits its service request to the cloud service provider with the connection of Internet or wired/wireless networks. The result of the requested service is delivered back to the user in time, whereas the information storage and process, interoperating protocols, service composition, communications and distributed computing, are all smoothly interactive by the networks. In this study, this is a survey on GCC schemes based on networks. The concept and history of Green computing were introduced first, and then focus on the challenge and requirement of cloud computing. Cloud computing needs to become green, which means provisioning cloud service while considering energy consumption under a set of energy consumption criteria and it is called GCC. Furthermore, the recent work done in GCC based on networks, including microprocessors, task scheduling algorithms, virtualisation technology, cooling systems, networks and disk storage were introduced. After that, the works on GCC from their research group was presented in Georgia State University. Finally, the conclusion and some future works were given. - Author(s): R. Hussain ; F. Kappel ; F. Zhu ; N.W. Levin ; P. Kotanko
- Source: IET Communications, Volume 6, Issue 18, p. 3301 –3308
- DOI: 10.1049/iet-com.2011.0187
- Type: Article
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Dialysis patients with high body mass index (BMI) experience survival advantages as compared to dialysis patients with low BMI. Preliminary modelling results seem to confirm the dependence of survival probabilities on BMI, but also show that BMI is a too crude measure. The simulation results strongly indicate that body composition instead of BMI is the important factor. The purpose of this study is to confirm these findings by simulations with a mathematical model using concrete data concerning body composition. In addition, the authors present the results of a sensitivity analysis for the parameters of the model, which are confirmed by the results of parameter estimation procedures. - Author(s): H. Xiong ; C. Li ; Q. Dai ; S. Fu
- Source: IET Communications, Volume 6, Issue 18, p. 3309 –3314
- DOI: 10.1049/iet-com.2012.0126
- Type: Article
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In this study, the authors propose a new concept named similar-bent function and the authors present two general methods to construct balanced sequences with low correlation by using similar-bent functions and orthogonal similar-bent functions. The authors find that the bent sequence sets are special cases of our construction. The authors also investigate the linear complexity of the new constructed sequences. If a suitable similar-bent function is given, the sequences constructed by it can have high-linear complexity. As examples, the authors construct two new low-correlation sequence sets. One constructed based on Dobbertin's iterative function is asymptotically optimal with respect to the Welch bound and the other one is constructed based on Kasami function whose sequences have a high-linear complexity. - Author(s): K.A. Darabkh ; I.F. Jafar ; G.A. Sukkar ; G.A. Abandah ; R. Al-Zubi
- Source: IET Communications, Volume 6, Issue 18, p. 3315 –3328
- DOI: 10.1049/iet-com.2012.0410
- Type: Article
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The convolutional coding is a very popular channel coding technique for the major reason of mitigating the probability of having many retransmissions because of difficult (noisy) communication channels. Sequential decoding is a type of convolutional codes that becomes of interest in wireless communication since it affords a decoding time that can be adaptive to channel state. In this study, the authors propose an improved queuing model, using discrete-time semi-Markov chain, which represents a modified packet retransmission policy over previously proposed queuing model. The authors queuing model mainly describes the behaviour of the buffer, which belongs to intermediate hops, when sequential decoding is implemented and concerns also about packets being transmitted over erroneous channels. The authors aim after conducting queuing analysis to find a real mathematical form for the average buffer occupancy as a network performance metric. Although the improved queuing model when incorporating the new policy for retransmission is very complicated, we are finally able to derive an expression for that performance metric considering practical assumptions. They further illustrate how the modified queuing model has a better impact on the end-to-end delay of messages, being transmitted without any extra buffering requirements needed, than the other relevant proposed queuing model. They conduct a simulation study using computer programming with the same assumptions used for queuing analysis to validate their analytical explanations and results. Furthermore, they validate the correctness of their closed-form expression through comparing its results with those obtained from expression related to a queuing model which discarded employing any retransmission policy. - Author(s): B. Rassouli and A. Olfat
- Source: IET Communications, Volume 6, Issue 18, p. 3329 –3338
- DOI: 10.1049/iet-com.2012.0113
- Type: Article
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Spectrum sensing is one of the main features of cognitive radio that enables secondary users (SUs) to detect spectrum holes. In this study, the authors propose a more realistic measure of interference which is based on the collision between secondary and primary signals. Considering the single SU scenario, the authors find optimal sensing time, transmission time and energy detector threshold to maximise its efficiency while keeping its interference on primary users below a certain threshold. Then, cooperative sensing schemes in a centralised network are investigated in which, the authors derive the optimal cooperation method in the Neyman–Pearson framework and subsequently propose simpler suboptimal cooperative schemes. Furthermore, the authors formulate the limited feedback scheme that uses a two bit quantiser for energy detectors, and compare its performance with other cooperation schemes and it will be shown to have the closest performance to the optimal scheme among all other mentioned methods. - Author(s): C.-D. Lee ; Y. Chang ; M.-H. Jing ; J.-H. Miao
- Source: IET Communications, Volume 6, Issue 18, p. 3339 –3349
- DOI: 10.1049/iet-com.2012.0180
- Type: Article
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Recently, the unified unknown syndrome representations to decode a class of binary cyclic codes have been developed by using Lagrange interpolation formula (discussed by Chang and Lee in 2010). In this study, a new method by combining the syndrome matrix search and modified Chinese remainder theorem is proposed to express the unified unknown syndrome representation as a rational function in terms of the known syndromes. A computer simulation has been executed to determine the syndrome matrices for binary cyclic codes of lengths less than or equal to 51. Compared to the Lagrange interpolation method, the method presented here substantially reduces the computational time for binary cyclic codes generated by irreducible polynomials. Finally, a complete decoding of the (31, 16, 7) quadratic residue code with inverse-free Berlekamp–Massey algorithm is given as an illustration. - Author(s): A.I. Sulyman ; Y. Al-Zahrani ; S. Al-Dosari ; A. Al-Sanie ; S. Al-Shebeili ; V. Tarokh
- Source: IET Communications, Volume 6, Issue 18, p. 3350 –3357
- DOI: 10.1049/iet-com.2012.0173
- Type: Article
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This study presents the analysis of a constellation partition (CP) algorithm for multiple-input multiple-output–maximum-likelihood detection (MIMO–MLD) systems. The authors consider an Nt by Nr MIMO system, where MLD algorithm is employed at the receiver side for MIMO signal detection. The authors show that for the case of orthogonal space-time block codes and MIMO beamforming (MIMO-BF) systems, the proposed CP algorithm achieves the same error-rate performance as the optimum MLD algorithm while cutting back significantly on the complexity of MIMO–MLD scheme. Thus complexity reduction is not achieved at the expense of the optimum MLD performance in these cases, unlike the existing simplified MLD schemes in the literature. For the case of MIMO-multiplexing system, however, it is observed that the complexity reduction is achieved at the expense of the optimum MLD performance, similar to the existing simplified MLD schemes. Thus the proposed algorithm is especially attractive in real-time implementation of space-time block code and MIMO-BF systems.
Optimality of transmitter location in a wireless network with RAKE receivers
On the design of full-rate full-diversity space-time block codes for multiple-input–multiple-output systems with a turbo minimum mean square error equaliser at the receiver side
Time-varying modulation systems
Subspace optimisation-based iterative interference alignment algorithm on the Grassmann manifold
On eigen-based signal combining using the autocorrelation coefficient
Adaptive M-ary quadrature amplitude spatial modulation
Optimal power allocation for decode-and-forward multihop relaying system with direct link
Multi-user multiple-input single-output downlink transmission systems exploiting statistical channel state information
On the cumulative distribution function of the sum and harmonic mean of two α−μ random variables with applications
Superimposed training design based on Bayesian optimisation for channel estimation in two-way relay networks
Efficient restarted radius bisection algorithm for sphere decoding with applications to multiple-in multiple-out systems
Superimposed training-based compressed sensing of sparse multipath channels
Soft decoding of the (23, 12, 7) Golay code: simplified algorithm and hardware implementation
Cooperative mobile-to-mobile communications over double Nakagami-m fading channels
Code acquisition of random optical codes in optical code-division multiple-access
Base station identification in single-frequency network positioning system under mixed line-of-sight/non-line-of-sight condition
Steepest descent algorithm implementation for multichannel blind signal recovery
Constant interference methods for power allocation in orthogonal frequency division multiplexing-based cognitive radio networks
Simulation and fabrication of blood filtration system for patients with kidney diseases
Unifying identity management for fourth generation wireless networks
Asymptotic capacity of opportunistic scheduling over gamma–gamma (generalised-K) composite fading channels
Service-oriented architecture structure for healthcare systems utilising vital signs
Fabrication and analysis of hollow microneedles and polymeric piezoelectric valveless micropump for transdermal drug-delivery system
Prediction of membrane protein types by using dipeptide and pseudo amino acid composition-based composite features
Neural network-based approach for the non-invasive diagnosis and classification of hepatotropic viral disease
Security mechanism for a wireless-sensor-network-based healthcare monitoring system
A data mining approach for fall detection by using k-nearest neighbour algorithm on wireless sensor network data
Privacy-preserving range set union for rare cases in healthcare data
Green cloud computing schemes based on networks: a survey
Body composition and solute kinetics in hemodialysis patients: a mathematical model
New constructions of low-correlation sequences with high-linear complexity
An improved queuing model for packet retransmission policy and variable latency decoders
Periodic spectrum sensing parameters optimisation in cognitive radio networks
New method of predetermining unified unknown syndrome representations for decoding binary cyclic codes
Two-stage constellation partition algorithm for reduced-complexity multiple-input multiple-output–maximum-likelihood detection systems
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