Massive multiple input multiple output (MIMO) plays a pivotal role in the fifth generation (5G) wireless networks. However, its performance heavily relies on accurate synchronization. Although timing offset (TO) can be avoided by applying orthogonal frequency division multiplexing (OFDM) with an adequate length of cyclic prefix (CP), carrier frequency offset (CFO) is still a challenging issue. Especially, in the uplink of multiuser massive MIMO systems, CFO compensation can impose a substantial amount of computational complexity to the base station (BS) due to the large number of BS antennas. To resolve this problem, in this paper, we propose a low-complexity CFO compensation technique. Our solution is performed after combining the received signals at the BS antennas. We calculate the interference matrix and discuss that asymptotically, this matrix can be obtained in terms of the power delay profile (PDP) of the users' channels. Consequently, the computational complexity of the CFO compensation process is independent of the number of BS antennas and thus remains constant as this number increases. Moreover, we show that the calculated interference matrix can be diagonalized due to its circulant property, and as a result, its inverse can be obtained straightforwardly. This leads to a considerable saving in the computational cost of the receiver. Numerical results are presented to verify the performance of our proposed CFO compensation technique and to investigate its computational complexity.
Massive multiple input multiple output (MIMO) plays a pivotal role in the fifth generation (5G) wireless networks. However, the carrier frequency offset (CFO) estimation is a challenging issue in the uplink of multiuser massive MIMO systems. In fact, frequency synchronization can impose a considerable amount of computational complexity to the base station (BS) due to a large number of BS antennas. In this paper, thanks to the properties of massive MIMO in the asymptotic regime, we develop a simple synchronization technique and derive a closed form equation for CFO estimation. We show that the phase information of the covariance matrix of the received signals is solely dependent on the users' CFOs. Hence, if a real-valued pilot is chosen, the CFO values can be straightforwardly calculated from this matrix. Hence, there is no need to deal with a complex optimization problem like the other existing CFO estimation techniques in the literature. Our simulation results testify the efficacy of our proposed CFO estimation technique. As we have shown, the performance of our method does not deteriorate as the number of users increases.
Massive multiple input multiple output (MIMO) is a key technology in the fifth generation (5G) wireless networks. However, its performance heavily relies on accurate synchronization. Additionally, synchronization can impose an enormous amount of computational complexity to the system. To deal with this issue, in this paper, we propose a low complexity frequency synchronization technique with a high accuracy for the uplink of multiuser orthogonal frequency division multiplexing (OFDM) based massive MIMO systems. First, we propose a carrier frequency offset (CFO) estimation whose computational complexity increases only linearly with respect to the number of base station (BS) antennas. Second, we propose a CFO compensation method that is performed after combining the received signals at the BS antennas, and as a result, its computational complexity is independent of the number of BS antennas. As a third contribution, the effect of the CFO estimation error is studied, and it is proven that by applying our proposed CFO compensation technique, the CFO estimation error causes only a constant phase shift. We then propose an algorithm to efficiently calculate and remove the estimation error. Our simulation results testify the efficacy of our proposed synchronization technique. As it is demonstrated, our proposed synchronization technique leads to a bit error rate (BER) performance that is very close to the one for a fully synchronous system.
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