# Performance Evaluation of GFDM Channel Estimation Using DFT for Tactile Internet Application
## 1 Introduction  
There are many new requirements in the 5 th generation (5G) cellular networks. They include high reliability and robustness, ultra-low latency, high data capacity and low out-of-band (OOB) emission [1; 2]. The ordinary orthogonal frequency division multiplexing (OFDM) framework has become unable to supply the above requirements. Tactile internet [2; 3; 4; 5] is one of several use-cases proposed for 5G networks requires ultra-low latency and high spectral efficiency. Sub-millisecond real-time reaction is the main challenge in tactile internet. If the round-trip delays between the command insertion are too large, then the response of devices will result in poor quality in experience (QoE). This requirement makes the overall frame size limited. It means that the forward error correction (FEC) length should be restricted. In addition, OFDM with one cyclic prefix (CP) per symbol leads to low spectral efficiency. There are some promising candidates to satisfy 5G network requirement. Universal filtered multi-carrier (UFMC) [6] is an OFDM based waveform that employ a short length filter to filter a set of subcarriers. These subcarriers remain orthogonal to each other. In order to combat intersymbol interference (ISI), UFMC does not use CP and employ zero-padding to provide the filter spreading. Hence, UFMC is more sensitive in term of time misalignment which resulting in performance loss. Another OFDM-based waveform is filtered orthogonal division multiplexing (F-OFDM) [7]. In F-OFDM, CP is employed to minimize ISI in multipath channels. F-OFDM is able to compress OOB radiation CP that can be used for synchronization without penalizing performance. Nevertheless, F-OFDM uses one CP per symbol, so reducing spectrum efficiency when short symbols are required. This constraint does not fit for tactile internet application. In an attempt to answer that challenge, GFDM comes as one of contender that is able to cover the requirements. The GFDM symbol can be compressed to reduce latency [8], while time-windowing and blank time slot [9] can be employed to reduce OOB even further. Amplitude and phase are varied in wireless channel due to their propagation characteristics. If these two parameters cannot be corrected in receiver, the resulted data cannot be recovered. Therefore, the propagation characteristics are important to be estimated in real time. By inserting pilot symbols at a known period, the restoration of transmitted data can be performed. This method has been proposed for GFDM system in [10]. Two well-known channel estimation methods--least square (LS) and linear minimum mean square error (LMMSE)--have been implemented [11; 12]. However, the opportunity to explore the performance of channel estimation using other techniques remains wide-open. Channel estimation using DFT has been used massively in OFDM and it offers better outcome to estimate the channels, rather than the LS or LMMSE [13; 14]. Thus, this motivated us to employ the subject method to GFDM system. A similar method also has been performed in a GFDM system [15]. However, the DFT-based channel estimation method is performed under 2-tap random channel in which this condition is not suitable for 5G scenarios. Moreover, the paper does not discuss about SER performance, which indicates how this method contributes to the enhancement of GFDM performance. The trade-off between data symbol and pilot symbol is not specified in the paper. Hence, in this study, we cover all the drawbacks of the paper and bring realistic case of 5G system as GFDM is one of contender for 5G networks. The only way to evaluate channel estimation using DFT is the length of channel impulse response (CIR) has to be identified correctly in the receiver and the length of channel tags shall be less than CP. Additionally, the recent work of hybrid multiple-input multiple-output (MIMO) GFDM system using millimeter-wave (mmWave) is discussed in [16]: two-step multi user equalization is evaluated in that paper. However, there is no channel estimation process discussed in the system.