In multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems, multi-user detection (MUD) algorithms play an important role in reducing the effect of multi-access interference (MAI). A combination of the estimation of channel and multi-user detection is proposed for eliminating various interferences and reduce the bit error rate (BER). First, a novel sparse based k-nearest neighbor classifier is proposed to estimate the unknown activity factor at a high data rate. The active users are continuously detected and their data are decoded at the base station (BS) receiver. The activity detection considers both the pilot and data symbols. Second, an optimal pilot allocation method is suggested to select the minimum mutual coherence in the measurement matrix for optimal pilot placement. The suggested algorithm for designing pilot patterns significantly improves the results in terms of mean square error (MSE), symbol error rate (SER) and bit error rate for channel detection. An optimal pilot placement reduces the computational complexity and maximizes the accuracy of the system. The performance of the channel estimation (CE) and MUD for the proposed scheme was good as it provided significant results, which were validated through simulations.Technologies 2018, 6, 72 2 of 16 low), the transmitting signal vector has a sparse property due to a large number of non-zero elements. Therefore, the decoding of the transmitted signal becomes a CS problem [7]. The long-term evolution is appropriate for a system that provides a small number of high activity of users. However, this shifts for machine-type communication (MTC) where a higher number of users with fewer activity sporadically sends a small number of packets [8].Recently, researchers have focused more on OFDM systems compared to the existing air-interface techniques due to its low complexity. In OFDM systems, the subcarriers are sent through multiple channels, which permits ease of equalization in the case of low complexity during the implementation.Spyridon et al.[9] considered various types of noises, such as Additive white Gaussian noise (AWGN), phase noise (PN), Rayleigh fading, Rician fading and Doppler shift with the turbo coding technique. The simulation platform consisted of three modules (transmitter, channel and receiver). In the transmitter module, turbo coding is performed, which makes the system more immune to the effects of noise with excellent BER results. The channel model is constituted by multipath fading, Doppler shift, AWGN and PN.In reference [10] the simulation is carried under various noise types, such as complex Rayleigh fading, complex Rician noise, AWGN and phase noise.Spyridon et al.[11] split an information stream into multiple frequency carriers, which joins OFDM in the simulation platform with turbo codes to find a better turbo scheme compared to a typical parallel concatenated convolutional codes and serial concatenated convolutional codes (PCCCs and SCCCs) are a class of Forward error correction codes suitabl...
: This article proposes active learning strategies for delivering engineering courses to the students in order to make learning more engaging, interesting, accomplishing, and joyful. The education system was impacted by the unprecedented situations generated by the Coronavirus pandemic from the last two academic years. The student community is also going through difficult situations on many levels. The primary challenge for teachers was to engage the students passionately in learning while maintaining a stress-free, healthy and fruitful environment in the online classes. For a stress-free teaching-learning process, adopting a variability in course content delivery methods would be a smart choice for teachers. This paper discusses the most effective active learning strategies in higher education. The work also highlights examples of implementation and an analysis of the effectiveness of active learning methodologies in terms of learners understanding, competency, satisfaction and knowledge gain. The findings indicate that the active learning strategy has assisted students in being more comfortable and engaged in effective learning in the online mode. Keywords :Active Teaching and Learning; Crossword; Higher Education; Mind map; Project Based Learning; Think pair share.
Nowadays, Multicarrier Direct sequence code division multiple access (MC DS-CDMA) systems are used in mobile communication. Performance of these systems are limited by multiple access interference (MAI) created by spread-spectrum users in the channel as well as background channel noise. This paper proposes an incremental gradient descent (IGD) multi-user detection (MUD) for MC DS-CDMA system that can achieve near-optimum performance while the number of users is linear in its implementation complexity. The IGD algorithm make an effort to perform optimum MUD by updating one user's bit decision each iteration in the best way. This algorithm accelerates the gradient algorithm convergence by averaging. When a minimum mean square error (MMSE) MUD is employed to initialize the proposed algorithm, in all cases tested the gradient search converges to a solution with optimum performance. Further, the iterative tests denote that the proposed IGD algorithm provides significant performance for cases where other suboptimum algorithms perform poorly. Simulation compares the proposed IGD algorithm with the conventional detectors.
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