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Emergence of modern multicore architectures has made runtime reconfiguration of system resources possible. All reconfigurable system resources constitute a design space and the proper selection of configuration of these resources to improve the system performance is known as Design Space Exploration (DSE). This reconfiguration feature helps in appropriate allocation of system resources to improve the efficiency in terms of performance, energy consumption, throughput, etc. Different techniques like exhaustive search of design space, architect’s experience, etc. are used for optimization of system resources to achieve desired goals. In this work, we hybridized two optimization algorithms, i.e., Genetic Algorithm (GA) and Estimation of Distribution Algorithm (EDA) for DSE of computer architecture. This hybrid algorithm achieved optimal balance between two objectives (minimal energy consumption and maximal throughput) by using decision variables such as number of cores, cache size and operating frequency. The final set of optimal solutions proposed by this GA–EDA hybrid algorithm is explored and verified by running different benchmark applications derived from SPLASH-2 benchmark suite on a cycle level simulator. The significant reduction in energy consumption without extensive impact on throughput in simulation results validate the use of this GA–EDA hybrid algorithm for DSE of multicore architecture. Moreover, the simulation results are compared with that of standalone GA, EDA and fuzzy logic to show the efficiency of GA–EDA hybrid algorithm.
Hira Waris; Ayaz Ahmad; Muhammad Yasir Qadri; Gulistan Raja; Tahir Nadeem Malik. GA–EDA: Hybrid Design Space Exploration Engine for Multicore Architecture. Journal of Circuits, Systems and Computers 2021, 1 .
AMA StyleHira Waris, Ayaz Ahmad, Muhammad Yasir Qadri, Gulistan Raja, Tahir Nadeem Malik. GA–EDA: Hybrid Design Space Exploration Engine for Multicore Architecture. Journal of Circuits, Systems and Computers. 2021; ():1.
Chicago/Turabian StyleHira Waris; Ayaz Ahmad; Muhammad Yasir Qadri; Gulistan Raja; Tahir Nadeem Malik. 2021. "GA–EDA: Hybrid Design Space Exploration Engine for Multicore Architecture." Journal of Circuits, Systems and Computers , no. : 1.
Single carrier frequency division multiple access (SC-FDMA) is a promising uplink transmission technique that has the characteristic of low peak to average power ratio. The mobile terminal uplink transmission depends on the batteries with limited power budget. Moreover, the increasing number of mobile users needs to be accommodated in the limited available radio spectrum. Therefore, efficient resource allocation schemes are essential for optimizing the energy consumption and improving the spectrum efficiency. This chapter presents a comprehensive and systematic survey of resource allocation in SC-FDMA networks. The survey is carried out under two major categories that include centralized and distributed approaches. The schemes are also classified under various rubrics including optimization objectives and constraints considered, single-cell and multi-cell scenarios, solution types, and perfect/imperfect channel knowledge-based schemes. The advantages and limitations pertaining to these categories/rubrics have been highlighted, and directions for future research are identified.
Muhammad Irfan; Ayaz Ahmad; Raheel Ahmed. Resource Allocation Techniques for SC-FDMA Networks. Design Methodologies and Tools for 5G Network Development and Application 2021, 121 -156.
AMA StyleMuhammad Irfan, Ayaz Ahmad, Raheel Ahmed. Resource Allocation Techniques for SC-FDMA Networks. Design Methodologies and Tools for 5G Network Development and Application. 2021; ():121-156.
Chicago/Turabian StyleMuhammad Irfan; Ayaz Ahmad; Raheel Ahmed. 2021. "Resource Allocation Techniques for SC-FDMA Networks." Design Methodologies and Tools for 5G Network Development and Application , no. : 121-156.
Due to the exponential rise in the number of subscribers in existing wireless networks, energy‐efficient distribution and utilization of network resources have become the preliminary objective of researchers nowadays. Nonorthogonal multiple access (NOMA) has attained widespread significance in this regard and has become a strong candidate for enhancing energy efficiency (EE) performance of existing networks. Multicarrier NOMA (MC‐NOMA) technique is an extension of NOMA that breaks the available resource block into various subchannels and allocates them efficiently to NOMA users (NUs). MC‐NOMA networks have the ability to further enhance system performance by efficiently exploiting channel diversity for addressing the problems of spectral inefficiency and power limitations. Therefore, in this paper, we have considered MC‐NOMA technology for an uplink scenario to investigate its performance for enhancing system EE by performing energy‐efficient power and subchannel allocation. To this end, we have formulated a joint user clustering, subchannel allocation, and power allocation problem for EE maximization (JSPEE) of uplink MC‐NOMA scenario. Due to the nonconvex, combinatorial nature of the problem, we propose a two‐step solution: that is, for each subchannel, first, subchannel allocation and user clustering are attained through low‐complexity suboptimal algorithm, which is followed by energy‐efficient power allocation of NUs. For subchannel allocation and user clustering, we exploit the channel diversity in the form of difference in channel gain values of various users. For power allocation, the nonconvex nature of the formulated problem is tackled by employing Dinkelbach and successive convex approximation (SCA) techniques to attain an energy‐efficient solution. Our simulation results portray that the JSPEE algorithm clearly outperforms the current NOMA as well as OMA works and enhances the system EE by efficient user clustering and exploiting channel diversity.
Bushra Rashid; Ayaz Ahmad; Sajid Saleem; Aimal Khan. Joint energy efficient power and subchannel allocation for uplink MC-NOMA networks. International Journal of Communication Systems 2020, e4606 .
AMA StyleBushra Rashid, Ayaz Ahmad, Sajid Saleem, Aimal Khan. Joint energy efficient power and subchannel allocation for uplink MC-NOMA networks. International Journal of Communication Systems. 2020; ():e4606.
Chicago/Turabian StyleBushra Rashid; Ayaz Ahmad; Sajid Saleem; Aimal Khan. 2020. "Joint energy efficient power and subchannel allocation for uplink MC-NOMA networks." International Journal of Communication Systems , no. : e4606.
The limited caching capacity of the local cache enabled Base station (BS) decreases the cache hit ratio (CHR) and user satisfaction ratio (USR). However, Cache enabled multi-tier cellular networks have been presented as a promising candidate for fifth generation networks to achieve higher CHR and USR through densification of networks. In addition to this, the cooperation among the BSs of various tiers for cached data transfer, intensify its significance many folds. Therefore, in this paper, we consider maximization of CHR and USR in a multi-tier cellular network. We formulate a CHR and USR problem for multi-tier cellular networks while putting major constraints on caching space of BSs of each tier. The unsupervised learning algorithms such as K-mean clustering and collaborative filtering have been used for clustering the similar BSs in each tier and estimating the content popularity respectively. A novel scheme such as cluster average popularity based collaborative filtering (CAP-CF) algorithm is employed to cache popular data and hence maximizing the CHR in each tier. Similarly, two novel methods such as intra-tier and cross-tier cooperation (ITCTC) and modified ITCTC algorithms have been employed in order to optimize the USR. Simulations results witness, that the proposed schemes yield significant performance in terms of average cache hit ratio and user satisfaction ratio compared to other conventional approaches.
Fawad Ahmad; Ayaz Ahmad; Irshad Hussain; Peerapong Uthansakul; Suleman Khan. Cooperation Based Proactive Caching in Multi-Tier Cellular Networks. Applied Sciences 2020, 10, 6145 .
AMA StyleFawad Ahmad, Ayaz Ahmad, Irshad Hussain, Peerapong Uthansakul, Suleman Khan. Cooperation Based Proactive Caching in Multi-Tier Cellular Networks. Applied Sciences. 2020; 10 (18):6145.
Chicago/Turabian StyleFawad Ahmad; Ayaz Ahmad; Irshad Hussain; Peerapong Uthansakul; Suleman Khan. 2020. "Cooperation Based Proactive Caching in Multi-Tier Cellular Networks." Applied Sciences 10, no. 18: 6145.
Sadiq Ahmad; Muhammad Naeem; Ayaz Ahmad. Unified optimization model for energy management in sustainable smart power systems. International Transactions on Electrical Energy Systems 2020, 30, 1 .
AMA StyleSadiq Ahmad, Muhammad Naeem, Ayaz Ahmad. Unified optimization model for energy management in sustainable smart power systems. International Transactions on Electrical Energy Systems. 2020; 30 (4):1.
Chicago/Turabian StyleSadiq Ahmad; Muhammad Naeem; Ayaz Ahmad. 2020. "Unified optimization model for energy management in sustainable smart power systems." International Transactions on Electrical Energy Systems 30, no. 4: 1.
The device-to-device (D2D) enabled cloud radio access network (C-RAN) is considered as a promising network model which provides high data rate and energy efficiency. In this paper, we formulate a joint mode selection, subchannel assignment (SA), power allocation (PA) and remote radio head (RRH)-association problem in D2D enabled single carrier frequency division multiple access based C-RAN in the uplink. This problem is mixed-integer non-linear problem which is extremely difficult to solve in its original form. To solve this problem, we propose an iterative technique which solves this problem in two stages; mode selection stage and joint SA, PA and RRH-association (SAPARA) stage. For mode selection, a link quality based technique is presented while, for joint SAPARA, we developed an iterative technique that solves this this problem in three steps such that SA and PA are carried out in the first and second step, respectively, while RRH-association is performed in the third step. Our results show the efficiency of the presented techniques.
Sher Ali; Ayaz Ahmad; Yasir Faheem; Muhammad Altaf; Habib Ullah. Energy-efficient RRH-association and resource allocation in D2D enabled multi-tier 5G C-RAN. Telecommunication Systems 2019, 74, 129 -143.
AMA StyleSher Ali, Ayaz Ahmad, Yasir Faheem, Muhammad Altaf, Habib Ullah. Energy-efficient RRH-association and resource allocation in D2D enabled multi-tier 5G C-RAN. Telecommunication Systems. 2019; 74 (2):129-143.
Chicago/Turabian StyleSher Ali; Ayaz Ahmad; Yasir Faheem; Muhammad Altaf; Habib Ullah. 2019. "Energy-efficient RRH-association and resource allocation in D2D enabled multi-tier 5G C-RAN." Telecommunication Systems 74, no. 2: 129-143.
In the literature, several variants of cat swarm optimization (CSO) algorithm are reported. However, CSO for integer multiobjective optimization problems (MOPs) has not yet been investigated. Owing to the frequent occurrence of integer MOPs and their importance in practical design problems, in this work, we investigate a new CSO approach for solving purely integer MOPs. This new approach named as multiobjective integer cat swarm optimization (MO-ICSO) algorithm incorporates the modified version of the CSO algorithm for MOPs. This approach is comprised of the concepts of rounding the floating points to the nearest integer numbers and the probabilistic updating (PU) technique. It uses the idea of Pareto dominance for finding the non-dominated solutions and an external archive for storing these solutions. We demonstrate the power of this new approach via its quantitative analysis and sensitivity test of its several parameters using different performance metrics performed over multiobjective multidimensional knapsack problem and several standard test functions. The simulation results argue that the proposed MO-ICSO approach can be a better candidate for solving the integer MOPs.
Shahid Ali Murtza; Ayaz Ahmad; Jawad Shafique. Integer cat swarm optimization algorithm for multiobjective integer problems. Soft Computing 2019, 24, 1927 -1955.
AMA StyleShahid Ali Murtza, Ayaz Ahmad, Jawad Shafique. Integer cat swarm optimization algorithm for multiobjective integer problems. Soft Computing. 2019; 24 (3):1927-1955.
Chicago/Turabian StyleShahid Ali Murtza; Ayaz Ahmad; Jawad Shafique. 2019. "Integer cat swarm optimization algorithm for multiobjective integer problems." Soft Computing 24, no. 3: 1927-1955.
Now days, distribution system has experienced numerous significant changes due to the implementation of smart grid technology and integration of distributed and renewable energy resources. Optimal integration of distributed generators and reconfiguration of the radial network have overall positive impacts on the power system. In this paper our aim is to minimize line losses and total harmonic distortion (THD), and to improve the voltage profile of the system by optimal placement and sizing of distributed generators and optimal reconfiguration of the network simultaneously. The impact of total harmonic distortion on power factor is also evaluated in this paper. Genetic algorithm is used as a solving tool to find optimal size of distributed generators and optimal reconfiguration of the network in a varying load environment. Placement buses for distributed generators are found by sensitivity analysis of the network. Fast harmonic load flow analysis and forward/backward sweep methods based on bus current injection to branch current (BIBC) matrix and branch current to bus voltage (BCBV) matrix are developed according to the network topology. The methodology is executed on IEEE-33 bus radial distribution system and the results shows its effectiveness.
Faheem Ud Din; Ayaz Ahmad; Hameed Ullah; Aimal Khan; Tariq Umer; Shaohua Wan. Efficient sizing and placement of distributed generators in cyber-physical power systems. Journal of Systems Architecture 2019, 97, 197 -207.
AMA StyleFaheem Ud Din, Ayaz Ahmad, Hameed Ullah, Aimal Khan, Tariq Umer, Shaohua Wan. Efficient sizing and placement of distributed generators in cyber-physical power systems. Journal of Systems Architecture. 2019; 97 ():197-207.
Chicago/Turabian StyleFaheem Ud Din; Ayaz Ahmad; Hameed Ullah; Aimal Khan; Tariq Umer; Shaohua Wan. 2019. "Efficient sizing and placement of distributed generators in cyber-physical power systems." Journal of Systems Architecture 97, no. : 197-207.
With the rapid increase in data traffic and high data rate demands from cellular users, conventional cellular networks are becoming insufficient to fulfill these requirements. Femto cells are integrated in macro cellular network to increase the capacity, coverage, and to fulfill the increasing demands of the users. Time required for handoff process between the cells became more sensitive and complex with the introduction of femto cells in the network. Public internet which connect the femto base station with the mobile core network induces higher latency if conventional handoff procedures are also employed in macro-femto cell network. So, handoff process will become slower and network operation will become insufficient. Some standards, procedures, and protocols should be defined for macro-femto cell network rather than using existing protocols. This chapter presents a comprehensive survey of handoff process, types of handoff in macro-femto cell network, and proposed methods and schemes for frequent and unnecessary handoff reduction for efficient network operation.
Muhammad Faheem Mustafa; Ayaz Ahmad; Raheel Ahmed. Handoff Management in Macro-Femto Cellular Networks. Design Methodologies and Tools for 5G Network Development and Application 2019, 227 -249.
AMA StyleMuhammad Faheem Mustafa, Ayaz Ahmad, Raheel Ahmed. Handoff Management in Macro-Femto Cellular Networks. Design Methodologies and Tools for 5G Network Development and Application. 2019; ():227-249.
Chicago/Turabian StyleMuhammad Faheem Mustafa; Ayaz Ahmad; Raheel Ahmed. 2019. "Handoff Management in Macro-Femto Cellular Networks." Design Methodologies and Tools for 5G Network Development and Application , no. : 227-249.
There are a number of algorithms for the solution of continuous optimization problems. However, many practical design optimization problems use integer design variables instead of continuous. These types of problems cannot be handled by using continuous design variables-based algorithms. In this paper, we present a multi-objective integer melody search optimization algorithm (MO-IMS) for solving multi-objective integer optimization problems, which take design variables as integers. The proposed algorithm is a modified version of single-objective melody search (MS) algorithm, which is an innovative optimization algorithm, inspired by basic concepts applied in harmony search (HS) algorithm. Results show that MO-IMS has better performance in solving multi-objective integer problems than the existing multi-objective integer harmony search algorithm (MO-IHS). Performance of proposed algorithm is evaluated by using various performance metrics on test functions. The simulation results show that the proposed MO-IMS can be a better technique for solving multi-objective problems having integer decision variables.
Jawad Shafique; Ayaz Ahmad; Shahid Ali Murtza. A Multi-Objective Integer Melody Search Algorithm. Applied Artificial Intelligence 2018, 33, 208 -228.
AMA StyleJawad Shafique, Ayaz Ahmad, Shahid Ali Murtza. A Multi-Objective Integer Melody Search Algorithm. Applied Artificial Intelligence. 2018; 33 (3):208-228.
Chicago/Turabian StyleJawad Shafique; Ayaz Ahmad; Shahid Ali Murtza. 2018. "A Multi-Objective Integer Melody Search Algorithm." Applied Artificial Intelligence 33, no. 3: 208-228.
The curtailing of consumers’ peak hours demands and filling the gap caused by the mismatch between generation and utilization in power systems is a challenging task and also a very hot topic in the current research era. Researchers of the conventional power grid in the traditional power setup are confronting difficulties to figure out the above problem. Smart grid technology can handle these issues efficiently. In the smart grid, consumer demand can be efficiently managed and handled by employing demand-side management (DSM) algorithms. In general, DSM is an important element of smart grid technology. It can shape the consumers’ electricity demand curve according to the given load curve provided by the utilities/supplier. In this survey, we focused on DSM and potential applications of DSM in the smart grid. The review in this paper focuses on the research done over the last decade, to discuss the key concepts of DSM schemes employed for consumers’ demand management. We review DSM schemes under various categories, i.e., direct load reduction, load scheduling, DSM based on various pricing schemes, DSM based on optimization types, DSM based on various solution approaches, and home energy management based DSM. A comprehensive review of DSM performance metrics, optimization objectives, and solution methodologies is’ also provided in this survey. The role of distributed renewable energy resources (DERs) in achieving the optimization objectives and performance metrics is also revealed. The unpredictable nature of DERs and their impact on DSM are also exposed. The motivation of this paper is to contribute by providing a better understanding of DSM and the usage of DERs that can satisfy consumers’ electricity demand with efficient scheduling to achieve the performance metrics and optimization objectives.
Sadiq Ahmad; Ayaz Ahmad; Muhammad Naeem; Waleed Ejaz; Hyung Seok Kim. A Compendium of Performance Metrics, Pricing Schemes, Optimization Objectives, and Solution Methodologies of Demand Side Management for the Smart Grid. Energies 2018, 11, 2801 .
AMA StyleSadiq Ahmad, Ayaz Ahmad, Muhammad Naeem, Waleed Ejaz, Hyung Seok Kim. A Compendium of Performance Metrics, Pricing Schemes, Optimization Objectives, and Solution Methodologies of Demand Side Management for the Smart Grid. Energies. 2018; 11 (10):2801.
Chicago/Turabian StyleSadiq Ahmad; Ayaz Ahmad; Muhammad Naeem; Waleed Ejaz; Hyung Seok Kim. 2018. "A Compendium of Performance Metrics, Pricing Schemes, Optimization Objectives, and Solution Methodologies of Demand Side Management for the Smart Grid." Energies 11, no. 10: 2801.
The rapid growth of connected devices and multimedia applications intensify the needs of high data rate and energy‐efficient networks. Multitier heterogeneous cloud radio access networks have been presented as a capable candidate for fifth‐generation networks for much higher data rate and energy efficiency (EE) than fourth generation. Therefore, in this paper, we consider the EE maximization in the uplink of a single‐carrier frequency division multiple access–based multitier heterogeneous cloud radio access network. We formulate a joint subchannel assignment, power allocation, and remote radio head association problem for EE maximization. Single‐carrier frequency division multiple access introduces subchannel exclusivity and subchannel adjacency constraints. These constraints, respectively, ensure the allocation of a subchannel to a single user at a time and the allocation of multiple subchannels to a user only if they are adjacent. In addition, we put constraints on each user's minimum data rate and maximum transmit power. Due to the simultaneous consideration of these four constraints, the solution of the formulated problem becomes harder. Therefore, a three‐step algorithm is developed, which solves this problem in an iterative manner. Simulation results verify that our proposed algorithm significantly improve the EE of the network.
Sher Ali; Ayaz Ahmad; Aimal Khan. Energy-efficient resource allocation and RRH association in multitier 5G H-CRANs. Transactions on Emerging Telecommunications Technologies 2018, 30, e3521 .
AMA StyleSher Ali, Ayaz Ahmad, Aimal Khan. Energy-efficient resource allocation and RRH association in multitier 5G H-CRANs. Transactions on Emerging Telecommunications Technologies. 2018; 30 (1):e3521.
Chicago/Turabian StyleSher Ali; Ayaz Ahmad; Aimal Khan. 2018. "Energy-efficient resource allocation and RRH association in multitier 5G H-CRANs." Transactions on Emerging Telecommunications Technologies 30, no. 1: e3521.
Energy management in residential buildings is one of the major keys for achieving the ambitious goals of efficient energy consumption, minimum carbon footprint, and reduced consumers energy expenditures. In this paper, we propose a novel residential energy management (REM) approach that is different from the conventional approaches. We formulate a REM problem with the objective to maximize the consumers utility under various practical constraints that include human interaction factor, unavailability of power supply, consumers preferences, and priorities. These constraints involve very high number of binary decision variables and result in extremely high search space that renders the solution of the REM problem prohibitively difficult. The application of standard optimization methods to this problem either require huge computational complexity or cannot find its optimal solution. Therefore, to optimally solve this problem, we propose a novel approach where we convert the original problem into an equivalent mathematical model with reduced number of constraints and decision variables. This significantly reduces the solution space of the problem, and standard optimization methods can be used for finding its optimal solution. The simulation conforms that the solution of the reformulated equivalent problem obtains optimal solution to the original REM problem with remarkably reduced computational complexity.
Sadiq Ahmad; Muhammad Naeem; Ayaz Ahmad. Low complexity approach for energy management in residential buildings. International Transactions on Electrical Energy Systems 2018, 29, e2680 .
AMA StyleSadiq Ahmad, Muhammad Naeem, Ayaz Ahmad. Low complexity approach for energy management in residential buildings. International Transactions on Electrical Energy Systems. 2018; 29 (1):e2680.
Chicago/Turabian StyleSadiq Ahmad; Muhammad Naeem; Ayaz Ahmad. 2018. "Low complexity approach for energy management in residential buildings." International Transactions on Electrical Energy Systems 29, no. 1: e2680.
The end-to-end performance metric for a conventional relay network with chase combining is the total Signal-to-Noise Ratio (SNR) delivered at the destination. However, the accumulated mutual information at the destination is the most suitable metric for a relay network which performs code combining (incremental redundancy) instead of chase combining at the destination. This paper investigates the accumulated mutual information acquired at the destination in an Amplify-and-Forward (AF), Decode-and-Forward (DF), and Coded Cooperation (CC) relay network. So far, the analytical comparison of the accumulated mutual information for the different relaying protocols is not reported in the literature. In this paper, it is proved analytically that the mutual information of a relay network with coded cooperation is always greater than or equal to the mutual information of decode-and-forward and amplify-and-forward for the case when all the relays can decode successfully. Moreover, it is also shown that the mutual information of a network with coded cooperation is always greater than or equal to that of a decode-and-forward relay network.
Aimal Khan; Saad Rehman; Muhammad Abbas; Ayaz Ahmad. On the mutual information of relaying protocols. Physical Communication 2018, 30, 33 -42.
AMA StyleAimal Khan, Saad Rehman, Muhammad Abbas, Ayaz Ahmad. On the mutual information of relaying protocols. Physical Communication. 2018; 30 ():33-42.
Chicago/Turabian StyleAimal Khan; Saad Rehman; Muhammad Abbas; Ayaz Ahmad. 2018. "On the mutual information of relaying protocols." Physical Communication 30, no. : 33-42.
Multi-tier cloud-radio access networks (C-RANs) have been suggested as a promising network model in fifth generation (5G) wireless networks to provide high data rate, high spectral efficiency and high energy efficiency at low cost. However, to achieve the potential benefits of multi-tier C-RANs, it is important to design efficient resource allocation algorithms provided that the data rate of users is guaranteed. Therefore, in this paper, we considered the joint optimization of remote-radio-heads (RRH) association, sub-channel assignment and power allocation for network sum-rate maximization in singlecarrier frequency division multiple access (SC-FDMA)-based multi-tier C-RAN. Due to the exclusivity and adjacency constraints of SC-FDMA, the resource allocation problem becomes harder to solve, thus, the optimal solution is difficult for reasonably sized network. Therefore, we propose an iterative algorithm that solves this non-linear mixed-integer problem in two steps wherein the first step, power allocation and subchannel assignment are carried out while the second step of the proposed algorithm is concerned with the RRH-association. The iterative algorithm converges to efficient solution. The simulation results verify the effectiveness of our proposed algorithm.
Sher Ali; Ayaz Ahmad; Razi Iqbal; Sajid Saleem; Tariq Umer. Joint RRH-Association, Sub-Channel Assignment and Power Allocation in Multi-Tier 5G C-Rans. IEEE Access 2018, 6, 34393 -34402.
AMA StyleSher Ali, Ayaz Ahmad, Razi Iqbal, Sajid Saleem, Tariq Umer. Joint RRH-Association, Sub-Channel Assignment and Power Allocation in Multi-Tier 5G C-Rans. IEEE Access. 2018; 6 (99):34393-34402.
Chicago/Turabian StyleSher Ali; Ayaz Ahmad; Razi Iqbal; Sajid Saleem; Tariq Umer. 2018. "Joint RRH-Association, Sub-Channel Assignment and Power Allocation in Multi-Tier 5G C-Rans." IEEE Access 6, no. 99: 34393-34402.
Independent component analysis (ICA) is a technique of blind source separation (BSS) used for separation of the mixed received signals. ICA algorithms are classified into adaptive and batch algorithms. Adaptive algorithms perform well in time-varying scenario with high-computational complexity, while batch algorithms have better separation performance in quasistatic channels with low-computational complexity. Amongst batch algorithms, the gradient-based ICA algorithms perform well, but step size selection is critical in these algorithms. In this paper, an adaptive step size gradient ascent ICA (ASS-GAICA) algorithm is presented. The proposed algorithm is free from selection of the step size parameter with improved convergence and separation performance. Different performance evaluation criteria are used to verify the effectiveness of the proposed algorithm. Performance of the proposed algorithm is compared with the FastICA and optimum block adaptive ICA (OBAICA) algorithms for quasistatic and time-varying wireless channels. Simulation is performed over quadrature amplitude modulation (QAM) and binary phase shift keying (BPSK) signals. Results show that the proposed algorithm outperforms the FastICA and OBAICA algorithms for a wide range of signal-to-noise ratio (SNR) and input data block lengths.
Zahoor Uddin; Ayaz Ahmad; Muhammad Iqbal; Zeeshan Kaleem. Adaptive Step Size Gradient Ascent ICA Algorithm for Wireless MIMO Systems. Mobile Information Systems 2018, 2018, 1 -9.
AMA StyleZahoor Uddin, Ayaz Ahmad, Muhammad Iqbal, Zeeshan Kaleem. Adaptive Step Size Gradient Ascent ICA Algorithm for Wireless MIMO Systems. Mobile Information Systems. 2018; 2018 ():1-9.
Chicago/Turabian StyleZahoor Uddin; Ayaz Ahmad; Muhammad Iqbal; Zeeshan Kaleem. 2018. "Adaptive Step Size Gradient Ascent ICA Algorithm for Wireless MIMO Systems." Mobile Information Systems 2018, no. : 1-9.
Introduction of electric vehicles (EVs) or plug-in electric vehicles (PEVs) in the road transportation can significantly reduce the carbon emission. Hence, the demand of EVs is likely to increase in the near future. Large penetration of EVs will also ultimately result into high loads on the existing power grids. The controlled charging of EVs can have a significant impact on the power grid load, voltage, frequency, and power losses. In this paper, we have provided a comprehensive review of various energy optimization approaches used for EVs charging. Energy optimization approaches used for EVs not only enhance the battery life but also contribute in regulating the voltage and frequency. During EVs charging, various objective functions such as supporting the renewable energy sources, minimization of the peak load, energy cost, and maximization of the aggregator profit have also been studied from optimization perspectives. The controlled and an optimized EVs charging enhances the performance of EVs batteries and conserves the energy in the system by minimizing the load and power losses. The different EVs charging approaches such as centralized and distributed suited for different objective functions have also been studied and compared with respect to various optimization approaches.
Muhammad Amjad; Ayaz Ahmad; Mubashir Husain Rehmani; Tariq Umer. A review of EVs charging: From the perspective of energy optimization, optimization approaches, and charging techniques. Transportation Research Part D: Transport and Environment 2018, 62, 386 -417.
AMA StyleMuhammad Amjad, Ayaz Ahmad, Mubashir Husain Rehmani, Tariq Umer. A review of EVs charging: From the perspective of energy optimization, optimization approaches, and charging techniques. Transportation Research Part D: Transport and Environment. 2018; 62 ():386-417.
Chicago/Turabian StyleMuhammad Amjad; Ayaz Ahmad; Mubashir Husain Rehmani; Tariq Umer. 2018. "A review of EVs charging: From the perspective of energy optimization, optimization approaches, and charging techniques." Transportation Research Part D: Transport and Environment 62, no. : 386-417.
Smart grid is an emerging research field of the current decade. The distinguished features of the smart grid are monitoring capability with data integration, advanced analysis to support system control, enhanced power security and effective communication to meet the power demand. Efficient energy consumption and minimum costs are also included in the prodigious features of smart grid. The smart grid implementation requires intelligent interaction between the power generating and consuming devices that can be achieved by installing devices capable of processing data and communicating it to various parts of the grid. The efficiency of these devices is greatly dependent on the selection and implementation of the advance digital signal processing techniques. This paper provides a comprehensive survey on the applications of signal processing techniques in smart grids, plus the challenges and shortcomings of these techniques. Furthermore, this paper also outlines some future research directions related to applications of signal processing in smart grids.
Zahoor Uddin; Ayaz Ahmad; Aamir Qamar; Muhammad Altaf. Recent advances of the signal processing techniques in future smart grids. Human-centric Computing and Information Sciences 2018, 8, 2 .
AMA StyleZahoor Uddin, Ayaz Ahmad, Aamir Qamar, Muhammad Altaf. Recent advances of the signal processing techniques in future smart grids. Human-centric Computing and Information Sciences. 2018; 8 (1):2.
Chicago/Turabian StyleZahoor Uddin; Ayaz Ahmad; Aamir Qamar; Muhammad Altaf. 2018. "Recent advances of the signal processing techniques in future smart grids." Human-centric Computing and Information Sciences 8, no. 1: 2.
This chapter reviews prevailing methodologies and future techniques to optimize energy consumption. It discerns that smart grid provides better tools and equipment to control and monitor the consumer load, and optimize the energy consumption. Smart grid is essentially composed of smart energy equipment, advance metering infrastructure and Phasor Measurement Units (Synchrophaors) that helps to achieve optimized energy consumption. The chapter also places focus on demand side management and optimized energy consumption scheduling; and establishes that both, the utilities, as well as the users can play a vital role in intelligent energy consumption and optimization. The literature review also reveals smart protection, self-healing systems and off-peak operation result in minimizing transmission and distribution losses, as well as optimizing the energy consumption.
Sadiq Ahmad; Ayaz Ahmad; Raziq Yaqub; Information Resources Management Association. Optimized Energy Consumption and Demand Side Management in Smart Grid. Smart Technologies 2018, 550 -574.
AMA StyleSadiq Ahmad, Ayaz Ahmad, Raziq Yaqub, Information Resources Management Association. Optimized Energy Consumption and Demand Side Management in Smart Grid. Smart Technologies. 2018; ():550-574.
Chicago/Turabian StyleSadiq Ahmad; Ayaz Ahmad; Raziq Yaqub; Information Resources Management Association. 2018. "Optimized Energy Consumption and Demand Side Management in Smart Grid." Smart Technologies , no. : 550-574.
Most of recent research in multicore processor architectures has been shifted towards reconfigurable architectures due to increasing complexity of computing systems. These systems provide better application-specific energy and throughput balance with their reconfigurable behavior. They perform automatic run time resource allocation for an application as per its needs. But in terms of performance, current methodologies produce some unpredictable results because of the actual variety of the workloads. Therefore, we need optimization of the system resources usage by employing some optimization algorithms. Early research in the field of reconfigurable architecture using optimization algorithms has produced efficient results for energy consumption with the reconfiguration of cache sizes and associativity, number of cores and operating frequency. In this research, we propose particle swarm optimization (PSO) based algorithm, Integer PSO (IPSO) for design space exploration of reconfigurable computer architectures to have better energy and throughput balance. The results obtained by IPSO are evaluated by using various SPLASH-2 benchmark applications. Evaluation shows notable reduction in energy consumption without major effect on throughput. Simulation results also support the use of IPSO in design space exploration of multicore reconfigurable processor architectures.
Shahid Ali Murtza; Ayaz Ahmad; Muhammad Yasir Qadri; Jameel Ahmed. Optimizing energy and throughput for MPSoCs: an integer particle swarm optimization approach. Computing 2017, 100, 227 -244.
AMA StyleShahid Ali Murtza, Ayaz Ahmad, Muhammad Yasir Qadri, Jameel Ahmed. Optimizing energy and throughput for MPSoCs: an integer particle swarm optimization approach. Computing. 2017; 100 (3):227-244.
Chicago/Turabian StyleShahid Ali Murtza; Ayaz Ahmad; Muhammad Yasir Qadri; Jameel Ahmed. 2017. "Optimizing energy and throughput for MPSoCs: an integer particle swarm optimization approach." Computing 100, no. 3: 227-244.