Sharif Digital Repository

Channel equalization is a crucial part of the OFDM communications protocols, which in turn requires channel estimation. In this paper, we consider the problem of orthogonal pilot design in MIMO-OFDM systems for sparse channel estimation. The pilot design in MIMO scenarios compared to the conventional SISO case has the additional constraint that the capability of recovery should be uniformly provided for all single channels. For instance, perfect estimation of a channel at the cost of another one is not permitted. This requirement is even more significant in the emerging Massive-MIMO systems. Our pilot design is based on the compressed sensing technique of minimizing the coherence measure of... 

We study the pilot design problem for sparse channel estimation in OFDM systems where multiple channels are estimated at a single antenna receiver. Such design is applicable to downlink of massive-MIMO systems and also to scenarios where multiple users transmit to a base station at the same carrier frequency. In our design, we deviate from the conventional orthogonal pilot arrangements by assigning the same pilot subcarriers to all transmitters. In the proposed setting, the achieved improvement in spectral efficiency (by reducing pilot overhead) may come at the expense of a more challenging channel estimation block at the receiver. To address this challenge and distinguish between different... 

We consider the deterministic pilot design problem for sparse channel estimation in an Orthogonal Frequency Division Multiplexing (OFDM) system. Our design is based on minimizing the coherence measure of the Fourier submatrix associated with the pilot subcarriers. This is done by optimizing over both pilot locations and pilot powers. As finding such global minimizer is a combinatorial problem, we resort to a greedy pilot allocation method. The resulting method achieves a suboptimal solution in a sequential manner and with reasonable computational complexity. Simulation results demonstrate that the proposed scheme performs similar to the existing methods with significantly lower computational... 

This letter investigates the deterministic design of pilot power and pattern for sparse channel estimation in OFDM systems based on minimizing the coherence of the DFT sub-matrix. It has been suggested that the pilot pattern forming a cyclic difference set (CDS) or almost difference set (ADS) is optimal. So, we proposed a deterministic procedure that jointly optimized for pattern and power of pilots as a solution. First, pilot patterns forming CDS/ADS were gathered through a search. Then, the power was numerically allocated to the different pilots from all the patterns. Finally, the pilot pattern and power pair leading to minimum coherence was selected from the available pairs. Simulation... 

Recently, there has been a growing interest in estimation of sparse channels as they are observed in underwater acoustic and ultrawideband channels. In this paper we present a new Bayesian sparse channel estimation (SCE) algorithm that, unlike traditional SCE methods, exploits noise statistical information to improve the estimates. The proposed method uses approximate maximum a posteriori probability (MAP) to detect the non-zero channel tap locations while least square estimation is used to determine the values of the channel taps. Computer simulations shows that the proposed algorithm outperforms the existing algorithms in terms of normalized mean squared error (NMSE) and approaches... 

This letter proposes a sparse diffusion algorithm for 1-bit compressed sensing (CS) in wireless sensor networks, and the algorithm is inherently robust against impulsive noise. The approach exploits the diffusion strategy from distributed learning in the 1-bit CS framework. To estimate a common sparse vector cooperatively from only the sign of measurements, a steepest descent method that minimizes the suitable global and local convex cost functions is used. A diffusion strategy is suggested for distributive learning of the sparse vector. A new application of the proposed algorithm to sparse channel estimation is also introduced. The proposed sparse diffusion algorithm is compared with both...