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![Figure 6. PAPR0 [dB] -Pr [PAPR > PAPR0] curves of the SLM, GA-SLM,...](publication/362548012/figure/fig5/AS:11431281091782379@1666614192842/PAPR0-dB-Pr-PAPR-PAPR0-curves-of-the-SLM-GA-SLM-BBO-SLM-and-CBBO-SLM-schemes-for_Q320.jpg)
High data rates, extremely low power consumption, and minimal end-to-end latency are considered to be mandatory requirements for 5G wireless networks. Rapid improvements in design and performance of 5G physical layer waveforms have become necessary. The drawback of Orthogonal Frequency Division Multiplexing (OFDM) is high PAPR, that causes signal d...
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... The use of MIMO techniques can further enhance the performance of GFDM systems. Multiple antennas have been mounted on the transmitter and receiver terminals to create the MIMO technology, which offers several advantages over single-input-single-output (SISO) systems [17]. ...
The future generation of wireless communications systems uses the generalized frequency division multiplexing (GFDM) due to its viable candidate waveform to perform multiple user scheduling. It is a non‐orthogonal waveform susceptible to intercarrier and intersymbol interference (ISI); still, it offers flexible pulse shaping that enhances the efficiency of user scheduling. Here, to accomplish spatial diversity, the multiple‐input multiple‐output (MIMO) is incorporated with GFDM to enhance the performance; there is also an extra inter‐antenna interference problem that limits the model's performance. The issue concerning inter‐antenna interference can be resolved by adopting pilot‐based information transfer. The detection of a signal at the receiver based on the minimum mean square error has the issue of computational complexity while enhancing the estimation quality of a detector. Hence, a low‐complexity channel estimation technique is proposed in this research using the V‐degree polynomial‐based channel estimation technique, wherein the cubic order computation is reduced to square order. Also, the proposed adaptive pulse shaping technique, wherein the filter coefficient is optimized using the gazelle optimization algorithm (GOA) to provide optimal pulse shaping filter parameters by employing bit error rate (BER) as the objective function. The performance of a proposed V‐degree polynomial‐based channel estimation is analyzed based on various assessment measures like BER and MSE and acquired the minimal values of 5.75E‐05 and 2.07E‐05, respectively.
... According to [13], an effective embedded SLM-PTS combination scheme (ESP) is one that splits the OFDM signal into smaller blocks, performs SLM steps in each sub-block, and then moves on to the next step with the results of each sub-block. In [14], the authors proposed that the SLM, based on the chaotic biogeography-based optimization (CBBO) algorithm, give a practical solution for the problem of high PAPR that appears in generalized frequency-division multiplexing waveforms. In [14], according to experimental results, the CBBO-SLM scheme greatly lowers PAPR when compared to conventional SLM methods like conventional GFDM and OFDM-SLM. ...
... In [14], the authors proposed that the SLM, based on the chaotic biogeography-based optimization (CBBO) algorithm, give a practical solution for the problem of high PAPR that appears in generalized frequency-division multiplexing waveforms. In [14], according to experimental results, the CBBO-SLM scheme greatly lowers PAPR when compared to conventional SLM methods like conventional GFDM and OFDM-SLM. In [15], in order to minimize the PAPR value, the authors use the SLM with several matrices, including the Greatest Common Divisor (GCD), Random, Riemann, Lehmer, and Hanowa. ...
... This section investigates how AGA can be used for phase optimization of SLM-OFDM system. In [11][12][13][14][15][16][17], GAs have been used for off-line tuning of the phase-rotation factors of PAPR. Although the used method finds suitable values, it takes a comparatively long time to do that. ...
In this paper, a new peak average power and time reduction (PAPTR) based on the adaptive genetic algorithm (AGA) strategy is used in order to improve both the time reduction and PAPR value reduction for the SLM OFDM and the conventional genetic algorithm (GA) SLM-OFDM. The simulation results demonstrate that the recommended AGA technique reduces PAPR by about 3.87 dB in comparison to SLM-OFDM. Comparing the suggested AGA SLM-OFDM to the traditional GA SLM-OFDM using the same settings, a significant learning time reduction of roughly 95.56% is achieved. The PAPR of the proposed AGA SLM-OFDM is enhanced by around 3.87 dB in comparison to traditional OFDM. Also, the PAPR of the proposed AGA SLM-OFDM is roughly 0.12 dB worse than that of the conventional GA SLM-OFDM.
... The SLM starts uplink transmission by converting the input data into the transmit signal using phase factor mapping and transmits various binary sequences with the lowest possible PAPR [17]. The phase factor can be optimized to lower PAPR with fewer searches and less complexity [18]. MTLBO is presented here to optimize the phase factor for LFDMA-SLM. ...
Localized Frequency Division Multiple Access (LFDMA) systems are gaining attention because of its low Peak to Average Power Ratio (PAPR). Selective Mapping (SLM) is one of the most widely used methods for achieving large PAPR reductions with minimal signal distortion. Traditional SLM optimization approaches such as Particle Swarm Optimization (PSO) and Simulated Annealing (SA) have constraints such as the demand for defined performance criteria, the reliance of solution quality on computation and a loss in efficiency for complex situations. In this paper, an SLM system based on Teaching–Learning Based Optimization (TLBO) is developed which substantially enhances PAPR performance without requiring computational preset parameters. The solutions produced by the teacher and learner phases of TLBO algorithm lack diversity, which may hamper the outcomes. In the proposed Modified Teaching–Learning Based Optimization (MTLBO), diversity learning is adopted in which students are sorted into groups prior to knowledge updating and the criteria for grouping in the two phases are fundamentally different. The MTLBO strategy fosters solution heterogeneity throughout the teaching and learning stages while decreasing local trapping and premature solution by applying diverse learning strategies in both phases along with differential learning and neighborhood learning for high-performing and low-performing students. Weights are also employed in some steps to enhance teaching and learning process. MTLBO-SLM-LFDMA systems utilizing Quadrature Phase Shift Keying (QPSK) and Quadrature Amplitude Modulation (QAM) schemes are compared to existing optimization strategies and the simulation results show that MTLBO-SLM-LFDMA outperforms existing approaches while ensuring good solution quality, better convergence and less computational effort.
... The results present an enhancement in the security of the audio encryption technique [13]. Kumar et al. used selective level mapping and chaotic biogeographybased optimization to optimize the GFDM PAPR performance [14]. This paper presents the behavior of GFDM in terms of OOB, spectral density, and BER by comparing it with OFDM. ...
... The pulse-shaped filter was applied for each subcarrier and circular convolution, to avoid using other samples. Pulse shapes of prototype filters give the system a new degree of freedom and can be optimized to give the best performance [13,14]. ...
The paper presents a novel approach for mitigating the detrimental effects of the high Peak-to-Average Power Ratio (PAPR) inherent in Non-Orthogonal Multiple Access (NOMA) waveforms using the Selective Mapping (SLM) technique. NOMA, a prominent multiple access scheme in modern wireless communication systems, facilitates concurrent transmission of multiple users over the same time-frequency resource. However, NOMA is susceptible to elevated PAPR, causing efficiency degradation and inter-symbol interference. The proposed method leverages SLM to address the PAPR challenges in NOMA waveforms. By generating a set of diverse phase sequences, SLM constructs alternative versions of the original NOMA signal. The phase sequence resulting in the lowest PAPR is then selected for transmission. This dynamic adaptation significantly reduces the peaks in the transmitted signal, thereby enhancing efficiency, minimizing distortion, and reducing the risk of nonlinear amplification. Extensive simulations are conducted to evaluate the efficiency of the projected procedure. The results demonstrate remarkable PAPR reduction in NOMA waveforms compared to conventional transmission methods. Additionally, the method maintains signal quality, improving the Bit Error Rate (BER), Power spectral density (PSD) and enhancing the overall reliability of the radio framework. The paper concludes with insights into the feasibility of integrating SLM into existing NOMA-enabled systems, offering a promising avenue for optimizing the efficacy of advanced radio networks.
Non-orthogonal multiple access (NOMA) is considered one of the most efficient waveforms for the beyond fifth-generation radio (B5GR) system. High peak-to-average power ratio (PAPR) is regarded as biggest drawbacks which degrades the efficiency of power amplifier (PA) in NOMA structure. Several algorithms were introduced to overcome the PAPR issue in multicarrier waveforms. The PAPR algorithms have successfully obtained an optimal PAPR value. However, the optimisation of PAPR also results in a degradation of bit error rate (BER) and an increase in computational complexity. In this letter, we presented a novel selective mapping (N-SLM) method to lower the high PAPR of the NOMA waveform without utilising the side information (SI). By generating an optimal phase rotation element, the PAPR and BER values of NOMA are reduced with a trivial increase in computational complexity.
Several techniques have been used to tackle the PAPR problem in Generalized Frequency Division Multiplexing (GFDM) systems. The Selective mapping (SLM) remains the most used alone or in combination with optimization algorithms in order to find optimal phase factors. Unfortunately, the complexity of implementation and the use of many control parameters are the main drawbacks of these techniques. This paper proposes an enhanced SLM technique to further improve the PAPR reduction in the GFDM system without increasing the system complexity. The proposed technique, i.e., JAYA-SLM, combines the JAYA algorithm with the SLM scheme. The simulation results demonstrate that the proposed JAYA-SLM technique is highly efficient in PAPR reduction without increasing the system complexity, wherein fewer used parameters. Also, it improves the system’s power saving and the Bit-Error-Rate (BER) performance when compared to others existing methods.
