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In this letter, we investigate time-domain channel estimation for wideband millimeter wave (mmWave) MIMO OFDM system. By transmitting frequency-domain pilot symbols as well as different beamforming vectors, we observe that the time-domain mmWave MIMO channels exhibit channel delay sparsity and especially block sparsity among different spatial directions. Then we propose a time-domain channel estimation exploiting block sparsity (TDCEBS) scheme, which always aims at finding the best nonzero block achieving the largest projection of the residue at each iterations. In particular, we evaluate the system performance using the QuaDRiGa which is recommended by 5G New Radio to generate wideband mmWave MIMO channels. The effectiveness of the proposed TDCEBS scheme is verified by the simulation results, as the proposed scheme outperforms the existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, we develop two high-resolution channel estimation schemes based on the estimating signal parameters via the rotational invariance techniques (ESPRIT) method for frequency-selective millimeter wave (mmWave) massive MIMO systems. The first scheme is based on two-dimensional ESPRIT (TDE), which includes three stages of pilot transmission. This scheme first estimates the angles of arrival (AoA) and angles of departure (AoD) and then pairs the AoA and AoD. The other scheme reduces the pilot transmission from three stages to two stages and therefore reduces the pilot overhead. It is based on one-dimensional ESPRIT and minimum searching (EMS). It first estimates the AoD of each channel path and then searches the minimum from the identified mainlobe. To guarantee the robust channel estimation performance, we also develop a hybrid precoding and combining matrices design method so that the received signal power keeps almost the same for any AoA and AoD. Finally, we demonstrate that the proposed two schemes outperform the existing channel estimation schemes in terms of computational complexity and performance. [ABSTRACT FROM AUTHOR]

Aiming at maximizing the achievable sum rate of wideband multiuser mmWave massive MIMO systems, hybrid precoding is studied. Since each computation of the achievable sum rate can be performed only after the analog precoder and the digital precoder are both determined, the maximization of the achievable sum rate has intractable computational complexity. By introducing the interference free (IF) achievable sum rate, the design of the analog and digital precoders can be decoupled. To avoid the beam conflict and maximize the IF achievable sum rate, a Hungarian-based codeword selection algorithm is proposed for the analog precoding design. The simulation results verify the effectiveness of the proposed scheme and show that a better performance can be achieved compared with the existing schemes. [ABSTRACT FROM AUTHOR]

Existing works design the pilot pattern for sparse channel estimation, assuming that the power of all pilots is equal. However, equal power allocation is not optimal in cognitive radio (CR) systems. In this correspondence, we jointly design the pilot power and pilot pattern for sparse channel estimation in orthogonal-frequency-division-multiplexing-based CR systems, based on the rule of mutual incoherence property that minimizes the coherence of the measurement matrix used for the sparse recovery. Under the sum power constraint and peak power constraint, the pilot design is formulated as a joint optimization problem, which is then decoupled into tractable sequential formations. Given a pilot pattern, we formulate the design of pilot power as a second-order cone programming. Then, we propose a joint design algorithm, which includes discrete optimization for pilot pattern and continuous optimization for pilot power. Simulation results show that the proposed algorithm can achieve better channel estimation performance in terms of mean square error and bit error rate and can further improve the spectrum efficiency by 2.4%, compared with existing algorithms assuming equal pilot power. [ABSTRACT FROM AUTHOR]

In this paper, we consider the pilot design based on the mutual incoherence property (MIP) for sparse channel estimation in orthogonal frequency-division multiplexing (OFDM) systems. With respect to the length of channel impulse response (CIR), we first derive a sufficient condition for the optimal pilot pattern generated from the cyclic different set (CDS). Since the CDS does not exist for most practical OFDM systems, we propose three pilot design schemes to obtain a near-optimal pilot pattern. The first two schemes, including stochastic sequential search (SSS) and stochastic parallel search (SPS), are based on the stochastic search. The third scheme called iterative group shrinkage (IGS) employs a tree-based searching structure and removes rows in a group instead of removing a single row at each step. We later extend our work to multiple-input–multiple-output (MIMO) systems and propose two schemes, i.e., sequential design scheme and joint design scheme. We also combine them to design the multiple orthogonal pilot patterns, i.e., using the sequential scheme for the first several transmit antennas and using the joint scheme to design the pilot pattern for the remaining transmit antennas. Simulation results show that the proposed SSS, SPS, and IGS converge much faster than the cross-entropy optimization and the exhaustive search and are thus more efficient. Moreover, SSS and SPS outperform IGS in terms of channel estimation performance. [ABSTRACT FROM PUBLISHER]

In this correspondence, sparse channel estimation is first introduced in orthogonal frequency-division multiplexing (OFDM)-based cognitive radio systems. Based on the results of spectrum sensing, the pilot design is studied by minimizing the coherence of the dictionary matrix used for sparse recovery. Then, it is formulated as an optimal column selection problem where a table is generated and the indexes of the selected columns of the table form a pilot pattern. A novel scheme using constrained cross-entropy optimization is proposed to obtain an optimized pilot pattern, where it is modeled as an independent Bernoulli random process. The updating rule for the probability of each active subcarrier selected as a pilot subcarrier is derived. A projection method is proposed so that the number of pilots during the optimization is fixed. Simulation results verify the effectiveness of the proposed scheme and show that it can achieve 11.5% improvement in spectrum efficiency with the same channel estimation performance compared with the least squares (LS) channel estimation. [ABSTRACT FROM PUBLISHER]

In this letter, we investigate the deterministic pilot allocation for sparse channel estimation in OFDM systems. Based on the rule of minimizing the coherence of the DFT submatrix, we derive that the pilot design according to the cyclic different set (CDS) is optimal. However, the CDS only exists for some specific number of OFDM subcarriers. For those cases where the CDS is unavailable, we propose a scheme using discrete stochastic approximation to obtain a near-optimal pilot pattern. Simulation results demonstrate that our scheme is much faster convergent and more efficient than the exhaustive search; and it has been shown that substantial improvement for channel estimation can be achieved. [ABSTRACT FROM PUBLISHER]