“…So we can use Eq. (20) to calculateĉ l , which means that the matrix operations used in WLS can be replaced by an arctangent function. This CPE ML estimation carries out the vector merging before arctangent calculation, which will reduce the information loss of multiple arctangent operations and thus improve the estimation performance.…”
Section: Proposed Algorithmmentioning
confidence: 99%
“…To compensate for the residual phase, several methods have been proposed. [18,19,20] introduced the ideal estimation, but it was too complex to implement. [21,22] only dealt with the CPE and ignored the STO, resulting in performance degradation for long frame.…”
In this paper, we propose a simplified weighted least square (SWLS) to estimate phase variations utilizing pilots, for Orthogonal Frequency Division Multiplexing (OFDM) based very high throughput wireless local area networks (WLANs). For SWLS, the common phase error (CPE) maximum likelihood (ML) estimation and the angle boundary treatment are improved to enhance the performance of phase estimation, while the combined scheme of pair pilots is used to reduce the complexity. Simulation results show that, compared to weighted least square (WLS) scheme, a similar pocket error rate (PER) is achieved by using the SWLS method, but more than 40 percent of complexity is reduced.
“…So we can use Eq. (20) to calculateĉ l , which means that the matrix operations used in WLS can be replaced by an arctangent function. This CPE ML estimation carries out the vector merging before arctangent calculation, which will reduce the information loss of multiple arctangent operations and thus improve the estimation performance.…”
Section: Proposed Algorithmmentioning
confidence: 99%
“…To compensate for the residual phase, several methods have been proposed. [18,19,20] introduced the ideal estimation, but it was too complex to implement. [21,22] only dealt with the CPE and ignored the STO, resulting in performance degradation for long frame.…”
In this paper, we propose a simplified weighted least square (SWLS) to estimate phase variations utilizing pilots, for Orthogonal Frequency Division Multiplexing (OFDM) based very high throughput wireless local area networks (WLANs). For SWLS, the common phase error (CPE) maximum likelihood (ML) estimation and the angle boundary treatment are improved to enhance the performance of phase estimation, while the combined scheme of pair pilots is used to reduce the complexity. Simulation results show that, compared to weighted least square (WLS) scheme, a similar pocket error rate (PER) is achieved by using the SWLS method, but more than 40 percent of complexity is reduced.
“…A number of CFO and SFO estimation algorithms have been studied throughout the years. These studied algorithms can be classified into two types: blind algorithms that do not use pilot symbols [7][8][9] and data-aided (DA) [10][11][12][13][14][15][16][17][18][19][20] algorithms using pilot symbols. Because of their simple form and computational convenience, DA methods have received more attention and are considered in this paper.…”
Section: Introductionmentioning
confidence: 99%
“…ML estimation requires at least a onedimensional exhaustive search and is not suitable for hardware implementation. Therefore, many DA suboptimal linear algorithms have been suggested [14][15][16][17][18]. A simple joint CFO and SFO estimation was presented in [14], where the value of the CFO was estimated for every symbol, but the SFO was derived from the early estimation of the CFO, resulting in a residual SFO and performance decrease.…”
Section: Introductionmentioning
confidence: 99%
“…A simple joint CFO and SFO estimation was presented in [14], where the value of the CFO was estimated for every symbol, but the SFO was derived from the early estimation of the CFO, resulting in a residual SFO and performance decrease. C. F. Dantas et al [15] presented a pilot frequency index-related SFO estimation method that neglected the different levels of fading of the pilot subcarriers and obtained a limited performance gain. [16] enabled robust estimation using a cyclic delay and pilot pattern to maximize the channel power.…”
A successive interference cancellation (SIC)-based weighted least-squares (WLS) estimation for the carrier frequency offset (CFO) and the sampling frequency offset (SFO) is presented for wireless local area networks (WLANs) based on orthogonal frequency division multiplexing (OFDM). The proposed SIC-based WLS performs the estimation by exploiting the phase rotation in the frequency domain caused by the CFO and the SFO. SIC-based WLS estimates the CFO and the SFO successively instead of by traditional simultaneous estimation. The estimation of CFO based on the Taylor series is performed first, and then the WLS estimation of SFO based on successive cancellation of the CFO is carried out. The simulation results show that the SIC-based WLS can estimate the CFO and the SFO effectively. Compared to the WLS scheme, a performance improvement of more than 0.6 dB is achieved by SIC-based WLS, and nearly 10 percent of the complexity is reduced.
SummaryThe rapid development of satellite internet networks has given rise to a new vision for the sixth generation of networking technology. However, the Doppler effect is relatively serious in satellite internet networks because a satellite moves quickly relative to a ground terminal. Therefore, there is an urgent need to study intelligent and dynamic synchronization methods to solve the problem of the rapidly changing Doppler frequency offset. Traditional methods do not consider the impact of spatial changes and typically focus on enhancing the estimation range or accuracy. We analyze various scenarios under phased array beam hopping and establish constraints between the terminal location, satellite ephemeris, subsatellite point track, elevation angle, and carrier frequency offset. We introduce dynamic game theory into frequency synchronization to optimize multiple Doppler estimation performance under rapidly changing channel conditions. We take the combination of carrier frequency offset estimation algorithm strategies at the current moment as the game entity. Simulation results demonstrate that the proposed method can achieve an estimation accuracy of 100 Hz and an estimation range of ±800 kHz. During the onboard test, the probability of achieving complete synchronization (when the synchronization success rate is 1) is 0.65, which is much higher than the 0.15 of the single method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.