# A Pilot-Based Integration Method of Ranging and LS Channel Estimation for OFDM Systems
## 1 Introduction  
Unmanned aerial vehicles (UAV) have been widely utilized in the civilian field owing to their advantages of low cost, flexibility and short mission period [1; 2; 3; 4]. To better meet the needs of different scenarios and improve the overall work efficiency and survivability, the main work form of the modern UAV system is multi-UAV cooperation [5; 6]. In addition to the ability to detect the target range, UAVs should be able to complete data transmission with cooperative UAVs and networks under the mode of multi-UAV cooperation [7]. Therefore, the integration of ranging and communication is a necessary function of UAV systems. The design of the integrated waveform is one of the crux elements in the study of communication systems that integrate ranging and communication, which can directly affect the receiving process. At present, the signal forms of integrated waveform design mainly include linear frequency modulation, spread spectrum, orthogonal frequency division multiplexing (OFDM) and other composite forms of one or more waveforms [8; 9; 10; 11; 12]. Among them, OFDM technology has received more attention and applications in high-speed communications and the integration of ranging and communications owing to its advantages of high spectrum efficiency, strong anti-interference ability and high data transmission rate [13; 14]. However, OFDM signals are susceptible to the channel in the variable and complex transmission environment of UAVs. The main approaches to solve this problem are channel estimation and equalization. The channel estimation is divided into three types: blind estimation, semi-blind estimation, and estimation based on the reference signal [15; 16]. Among them, blind channel estimation is an estimation method that does not require training sequences and utilizes only the statistical properties of the received signal and some properties of the transmitted signal for channel estimation [17; 18; 19; 20]. Semi-blind estimation is a channel estimation method based on blind estimation and requires a small number of pilots [21; 22; 23]. The channel estimation based on the reference signal is mainly performed by transmitting the pilot or guide signal for channel estimation and equalization [24; 25]. A subspace-based blind channel estimation method is proposed in [26], which can be applied to OFDM systems without changing the original transmitter. However, the subspace-based blind estimation method is prone to the problem of phase ambiguity. In [27], a semi-blind channel estimation method based on pseudo-random suffixes is investigated. This method avoids pilot overhead compared to known cyclic prefix pilot symbol-assisted modulation schemes. However, this method may suffer from error propagation problems. In the existing reference signal-based channel estimation methods, the minimum mean squared error (MMSE) and least squares (LS) techniques have attracted more attention [28; 29; 30; 31]. Among them, the LS channel estimation algorithm is less complex than the other algorithms. In [32], [PERSON] and [PERSON] et al. proposed a solution using low-complexity corrected LS channel estimation. Compared with the traditional LS, this method improves the mean square error performance of the improved LS channel estimation and the performance of the bit error rate (BER) system. In general, for the blind and semi-blind estimation, the final result of the channel estimation based on the reference signal is more closely matched to the actual situation of the channel [33]. However, this method requires the pilot to be inserted into the transmitted effective data in advance, which takes up information bits of the sent data, thus reducing the effectiveness and spectral efficiency of the transmitted data. To solve this problem, this paper innovatively improves the pilot utilization of the traditional LS estimation algorithm and proposes a method using pilot ranging to improve the frequency band utilization of LS channel estimation.