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Throughput Performance analysis of AMC based on New SNR Estimation Algorithm using Preamble

机译:基于Preamble的新型SNR估计算法的AMC吞吐量性能分析。

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The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation. Also, We applied AMC on several channel environments using the parameters of IEEE 802.11n, and compared the Throughput performance when using each of the different SNR Estimation Algorithms. The results obtained in the simulation confirm that the proposed algorithm produces the highest Throughput performance.
机译:用户数量的快速增长要求开发能够提供更高数据速率的可靠通信系统。为了满足这些要求,近年来已经开发了诸如多输入多输出(MIMO)和正交频分复用(OFDM)的技术。为了结合两种技术的优势,目前的研究活动集中在MIMO-OFDM系统上。另外,对于快速的无线信道环境,可以根据信道条件自适应地设置调制和编码来优化数据速率和可靠性。并使用副载波频率和功率分配技术。根据基于反馈的系统获得信道状态信息(CSI)并将其无延迟地反馈到发射机的准确性,整个系统的性能将很差或最佳。在本文中,我们提出了一种信噪比(SNR)估计算法,其中,前同步码对于收发器的两侧都是已知的。通过在多个信道环境下进行的仿真,我们证明了与传统的SNR估计相比,我们提出的SNR估计算法更加准确。此外,我们使用IEEE 802.11n的参数将AMC应用于多个信道环境,并比较了使用每种不同的SNR估计算法时的吞吐量性能。在仿真中获得的结果证实了该算法产生了最高的吞吐量性能。

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