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The pilot design problem in large-scale multi-input-multioutput orthogonal frequency division multiplexing (MIMO-OFDM) system is investigated from the perspective of compressed sensing (CS). According to the CS theory, the success probability of estimation is dependent on the mutual coherence of the reconstruction matrix. Specifically, the smaller...
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... Therefore, it is necessary to pursue the deterministic pilot design with superimposed pattern under the constraint of the required estimation performance. The deterministic pilot design with the superimposed pattern has been studied based on the mutual coherence criterion in [27][28][29]. Under the assumption of identical pilot sequence for different transmitters, [27] proposes a plot design for the estimation of high mobility channels. ...
... This assumption is impractical because it makes the estimation of each individual channel impossible. In [28], an alternating projection based scheme is proposed to allocate pilot symbols under the fixed locations. [27] and [28] only study the design of pilot symbols. ...
... In [28], an alternating projection based scheme is proposed to allocate pilot symbols under the fixed locations. [27] and [28] only study the design of pilot symbols. Besides the pilot symbol, the pilot location is also very important for pilot design. ...
To reduce the pilot overhead, compressive sensing techniques have been widely adopted for sparse channel estimation. In this paper, we explore the spatial common sparsity across different channels and investigate the deterministic pilot design with superimposed pattern for the downlink channel estimation in multi-input single-output systems. Previous works generally allocate pilots randomly when using the superimposed pilots to estimate the jointly sparse channels, which is storage-hungry and time-consuming. For the joint optimization of pilot locations and symbols, this paper proposes two pilot design schemes, named by Algorithms 1 and 2, to minimize the intrablock and interblock coherence simultaneously. Algorithm 1 sequentially optimizes pilot locations and symbols, while Algorithm 2 integrates the allocation of pilot symbols into the optimization of pilot locations and alternately optimizes the pilot locations and symbols. Both schemes can flexibly select the design criteria to ensure the small intrablock and interblock coherence. Simulation results show that the proposed pilot designs outperform the existing ones in terms of channel estimate mean-squared-error and bit-error-rate.
... e channel model is of great significance for the wireless communication system simulations and technology evaluations [1][2][3]. Meanwhile, the channel model standards, such as the 3GPP TR 36.873 ...
In this paper, the Gaussian mixture model (GMM) is introduced to the channel multipath clustering. In the GMM field, the expectation-maximization (EM) algorithm is usually utilized to estimate the model parameters. However, the EM widely converges into local optimization. To address this issue, a hybrid differential evolution (DE) and EM (DE-EM) algorithms are proposed in this paper. To be specific, the DE is employed to initialize the GMM parameters. Then, the parameters are estimated with the EM algorithm. Thanks to the global searching ability of DE, the proposed hybrid DE-EM algorithm is more likely to obtain the global optimization. Simulations demonstrate that our proposed DE-EM clustering algorithm can significantly improve the clustering performance.
... Both MIMO and OFDM are known to facilitate the wireless networks with excellent capabilities; when MIMO and OFDM are combined together, MIMO-OFDM achieves tremendous capacities that will be enjoyed by 5G systems in the near future. While MIMO-OFDM systems have superb performance, several challenges invoked by MIMO and OFDM characteristics are involved in the system design [1][2][3][4][5][6]. Other competing technologies in 5G networks are filtered-OFDM (F-OFDM) and universal filtered multicarrier (UFMC) that are receiving attention in the literature [7,8]. ...
... Without loss of generality, the weighting for the sum rate maximization is uniform in the simulations, that is, ( , ) = 1/ , ∀ , . We assume the power constraints are the same (1) Initialize: initialize (0), ∀ and ← 0; (2) while stopping criterion not met do (3) compute F ( , ), , ∀ , , using (28), (30); (4) solve for uà ( , ), , kà ( , ), , uB ( , ), , kB ( , ), , ∀ , , , using Corollary 4; (5) compute D̃I CI ( , ), , ∀ , , , using (63); (6) ( + 1) ← ( ) + ( ) ∑ , , ( , ) D̃I CI ( , ), , ∀ and ← + 1; (7) end while (8) for all BSs, that is, = , ∀ . Since the noise power was normalized to unity, the transmitter signal-to-noise ratio is SNR = 10 log 10 . ...
... However, we note that the gap between ICI-free system and system with ICI also increases with SNR. Full CSI method in [4], Υ = 0 Full CSI method in [4], Υ = 0.8 Stat. CSI Algorithm 1, Υ = 0 Stat. ...
With 5G communication systems on the horizon, efficient interference management in heterogeneous multicell networks is more vital than ever. This paper investigates the linear precoder design for downlink multicell multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems, where base stations (BSs) coordinate to reduce the interference across space and frequency. In order to minimize the overall feedback overhead in next-generation systems, we consider precoding schemes that require statistical channel state information (CSI) only. We apply the random matrix theory to approximate the ergodic weighted sum rate of the system with a closed form expression. After formulating the approximation for general channels, we reduce the results to a more compact form using the Kronecker channel model for which several multicarrier concepts such as frequency selectivity, channel tap correlations, and intercarrier interference (ICI) are rigorously represented. We find the local optimal solution for the maximization of the approximate rate using a gradient method that requires only the covariance structure of the MIMO-OFDM channels. Within this covariance structure are the channel tap correlations and ICI information, both of which are taken into consideration in the precoder design. Simulation results show that the rate approximation is very accurate even for very small MIMO-OFDM systems and the proposed method converges rapidly to a near-optimal solution that competes with networked MIMO and precoders based on instantaneous full CSI.
... Since pilot contamination occurs due to the reuse of same pilot sequences a way to combat it is to reorthogonalize the sequences. In various papers this has been along different dimensions: such as time and space [13]. Superimposed data and pilot transmission were proposed in [14]. ...
Massive Multiple-Input-Multiple-Output (M-MIMO) system is a promising technology that offers to mobile networks substantial increase in throughput. In Time-Division Duplexing (TDD), the uplink training allows a Base Station (BS) to acquire Channel State Information (CSI) for both uplink reception and downlink transmission. This is essential for M-MIMO systems where downlink training pilots would consume large portion of the bandwidth. In densely populated areas, pilot symbols are reused among neighboring cells. Pilot contamination is the fundamental bottleneck on the performance of M-MIMO systems. Pilot contamination effect in antenna arrays can be mitigated by treating the channel estimation problem in angular domain where channel sparsity can be exploited. In this paper, we introduce a codebook that projects the channel into orthogonal beams and apply Minimum Mean-Squared Error (MMSE) criterion to estimate the channel. We also propose data-aided channel covariance matrix estimation algorithm for angular domain MMSE channel estimator by exploiting properties of linear antenna array. The algorithm is based on simple linear operations and no matrix inversion is involved. Numerical results show that the algorithm performs well in mitigating pilot contamination where the desired channel and other interfering channels span overlapping angle-of-arrivals.
