List of Articles Complexity

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  1 - A New Finite Field Multiplication Algorithm to Improve Elliptic Curve Cryptosystem Implementations
  Abdalhossein Rezai Parviz Keshavarzi
  10.7508/jist.2013.02.006
  This paper presents a new and efficient implementation approach for the elliptic curve cryptosystem (ECC) based on a novel finite field multiplication in GF(2m) and an efficient scalar multiplication algorithm. This new finite field multiplication algorithm performs zer More

  This paper presents a new and efficient implementation approach for the elliptic curve cryptosystem (ECC) based on a novel finite field multiplication in GF(2m) and an efficient scalar multiplication algorithm. This new finite field multiplication algorithm performs zero chain multiplication and required additions in only one clock cycle instead of several clock cycles. Using modified (limited number of shifts) Barrel shifter; the partial result is also shifted in one clock cycle instead of several clock cycles. Both the canonical recoding technique and the sliding window method are applied to the multiplier to reduce the average number of required clock cycles. In the scalar multiplication algorithm of the proposed implementation approach, the point addition and point doubling operations are computed in parallel. The sliding window method and the signed-digit representation are also used to reduce the average number of point operations. Based on our analysis, the computation cost (the average number of required clock cycles) is effectively reduced in both the proposed finite field multiplication algorithm and the proposed implementation approach of ECC in comparison with other ECC finite field multiplication algorithms and implementation approaches. Manuscript profile
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  2 - Joint Relay Selection and Power Allocation in MIMO Cooperative Cognitive Radio Networks
  Mehdi  Ghamari Adian Hassan Aghaeenia
  10.7508/jist.2015.01.005
  In this work, the issue of joint relay selection and power allocation in Underlay MIMO Cooperative Cognitive Radio Networks (U-MIMO-CCRN) is addressed. The system consists of a number of secondary users (SUs) in the secondary network and a primary user (PU) in the prima More

  In this work, the issue of joint relay selection and power allocation in Underlay MIMO Cooperative Cognitive Radio Networks (U-MIMO-CCRN) is addressed. The system consists of a number of secondary users (SUs) in the secondary network and a primary user (PU) in the primary network. We consider the communications in the link between two selected SUs, referred to as the desired link which is enhanced using the cooperation of one of the existing SUs. The core aim of this work is to maximize the achievable data rate in the desired link, using the cooperation of one of the SUs which is chosen opportunistically out of existing SUs. Meanwhile, the interference due to the secondary transmission on the PU should not exceed the tolerable amount. The approach to determine the optimal power allocation, i.e. the optimal transmits covariance and amplification matrices of the SUs, and also the optimal cooperating SU is proposed. Since the proposed optimal approach is a highly complex method, a low complexity approach is further proposed and its performance is evaluated using simulations. The simulation results reveal that the performance loss due to the low complexity approach is only about 14%, while the complexity of the algorithm is greatly reduced. Manuscript profile
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  3 - Complexity Reduction in Massive-MIMO-NOMA SIC Receiver in Presence of Imperfect CSI
  Nilufar Tutunchi Afrooz Haghbin Behrad Mahboobi
  10.29252/jist.8.30.113
  One of the main reasons for switching to the next generation of communication systems is the demand of increasing capacity and network connections. This goal can be achieved using massive multiple input - multiple output (massive-MIMO) systems in combination with Non-or More

  One of the main reasons for switching to the next generation of communication systems is the demand of increasing capacity and network connections. This goal can be achieved using massive multiple input - multiple output (massive-MIMO) systems in combination with Non-orthogonal multiple access (NOMA) technique. NOMA technology uses the successive interference cancellation (SIC) receiver to detect user’s signals which imposes an additional complexity on the system. In this paper, we proposed two methods to reduce the system complexity. The proposed method despite imperfect channel state information (CSI) in the receiver, there is not significantly reduction in the system performance. Since the computation of matrices inverse has a high computational complexity, we used the Neumann series approximation method and the Gauss-Seidel decomposition method to compute matrices inverse in the SIC receiver. Simulation results are provided at the end of the paper in terms of bit error rate (BER) at the receiver which show, these methods have lower computational complexity in comparison with the traditional methods while they cause a slight performance reduction in the SIC receiver. Also, we examined the increasing and decreasing value of imperfect channel state information in the system performance which shows the increasing value of imperfect channel state information, cause a slight performance reduction in SIC receiver. Manuscript profile
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  4 - A Novel Elite-Oriented Meta-Heuristic Algorithm: Qashqai Optimization Algorithm (QOA)
  Mehdi Khadem Abbas Toloie Eshlaghy Kiamars Fathi Hafshejani
  10.52547/jist.34612.11.42.149
  20.1001.1.23221437.2023.11.42.8.5
  Optimization problems are becoming more complicated, and their resource requirements are rising. Real-life optimization problems are often NP-hard and time or memory consuming. Nature has always been an excellent pattern for humans to pull out the best mechanisms and th More

  Optimization problems are becoming more complicated, and their resource requirements are rising. Real-life optimization problems are often NP-hard and time or memory consuming. Nature has always been an excellent pattern for humans to pull out the best mechanisms and the best engineering to solve their problems. The concept of optimization seen in several natural processes, such as species evolution, swarm intelligence, social group behavior, the immune system, mating strategies, reproduction and foraging, and animals’ cooperative hunting behavior. This paper proposes a new Meta-Heuristic algorithm for solving NP-hard nonlinear optimization problems inspired by the intelligence, socially, and collaborative behavior of the Qashqai nomad’s migration who have adjusted for many years. In the design of this algorithm uses population-based features, experts’ opinions, and more to improve its performance in achieving the optimal global solution. The performance of this algorithm tested using the well-known optimization test functions and factory facility layout problems. It found that in many cases, the performance of the proposed algorithm was better than other known meta-heuristic algorithms in terms of convergence speed and quality of solutions. The name of this algorithm chooses in honor of the Qashqai nomads, the famous tribes of southwest Iran, the Qashqai algorithm. Manuscript profile