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Low-Complexity Modem Design for GFDM

机译:GFDM的低复杂度调制解调器设计

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Due to its attractive properties, generalized frequency division multiplexing (GFDM) is recently being discussed as a candidate waveform for the fifth generation of wireless communication systems (5G). GFDM is introduced as a generalized form of the widely used orthogonal frequency division multiplexing (OFDM) modulation scheme and since it uses only one cyclic prefix (CP) for a group of symbols rather than a CP per symbol, it is more bandwidth efficient than OFDM. In this paper, we propose novel modem structures for GFDM by taking advantage of the particular structure in the modulation matrix. Our proposed transmitter is based on modulation matrix sparsification through application of fast Fourier transform (FFT) to reduce the implementation complexity. A unified demodulator structure for matched filter (MF), zero forcing (ZF), and minimum mean square error (MMSE) receivers is also derived. The proposed demodulation techniques harness the special block circulant property of the matrices involved in the demodulation stage to reduce the computational cost of the system implementation. We have derived the closed forms for the ZF and MMSE receiver filters. Additionally, our algorithms do not incur any performance loss as they maintain the optimal performance. The computational costs of our proposed techniques are analyzed in detail and are compared with the existing solutions that are known to have the lowest complexity. It is shown that through application of our structures a substantial amount of computational complexity reduction can be achieved.
机译:由于其吸引人的特性,最近正在讨论将通用频分复用(GFDM)作为第五代无线通信系统(5G)的候选波形。 GFDM是作为广泛使用的正交频分复用(OFDM)调制方案的通用形式而引入的,由于它仅对一个符号组使用一个循环前缀(CP),而不是对每个符号使用CP,因此它比OFDM具有更高的带宽效率。在本文中,我们通过利用调制矩阵中的特定结构,为GFDM提出了新颖的调制解调器结构。我们提出的发射机基于调制矩阵稀疏度,通过应用快速傅立叶变换(FFT)来降低实现复杂性。还推导了用于匹配滤波器(MF),迫零(ZF)和最小均方误差(MMSE)接收器的统一解调器结构。所提出的解调技术利用了解调阶段所涉及的矩阵的特殊块循环特性,以降低系统实现的计算成本。我们导出了ZF和MMSE接收器滤波器的闭合形式。此外,我们的算法不会造成任何性能损失,因为它们可以保持最佳性能。我们对所提出技术的计算成本进行了详细分析,并与已知具有最低复杂性的现有解决方案进行了比较。结果表明,通过应用我们的结构,可以大大降低计算复杂度。

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