37 research outputs found
Joint Hybrid Precoder and Combiner Design for mmWave Spatial Multiplexing Transmission
Millimeter-wave (mmWave) communications have been considered as a key
technology for future 5G wireless networks because of the orders-of-magnitude
wider bandwidth than current cellular bands. In this paper, we consider the
problem of codebook-based joint analog-digital hybrid precoder and combiner
design for spatial multiplexing transmission in a mmWave multiple-input
multiple-output (MIMO) system. We propose to jointly select analog precoder and
combiner pair for each data stream successively aiming at maximizing the
channel gain while suppressing the interference between different data streams.
After all analog precoder/combiner pairs have been determined, we can obtain
the effective baseband channel. Then, the digital precoder and combiner are
computed based on the obtained effective baseband channel to further mitigate
the interference and maximize the sum-rate. Simulation results demonstrate that
our proposed algorithm exhibits prominent advantages in combating interference
between different data streams and offer satisfactory performance improvement
compared to the existing codebook-based hybrid beamforming schemes
Hybrid Precoder and Combiner Design with Low Resolution Phase Shifters in mmWave MIMO Systems
Millimeter wave (mmWave) communications have been considered as a key
technology for next generation cellular systems and Wi-Fi networks because of
its advances in providing orders-of-magnitude wider bandwidth than current
wireless networks. Economical and energy efficient analog/digial hybrid
precoding and combining transceivers have been often proposed for mmWave
massive multiple-input multiple-output (MIMO) systems to overcome the severe
propagation loss of mmWave channels. One major shortcoming of existing
solutions lies in the assumption of infinite or high-resolution phase shifters
(PSs) to realize the analog beamformers. However, low-resolution PSs are
typically adopted in practice to reduce the hardware cost and power
consumption. Motivated by this fact, in this paper, we investigate the
practical design of hybrid precoders and combiners with low-resolution PSs in
mmWave MIMO systems. In particular, we propose an iterative algorithm which
successively designs the low-resolution analog precoder and combiner pair for
each data stream, aiming at conditionally maximizing the spectral efficiency.
Then, the digital precoder and combiner are computed based on the obtained
effective baseband channel to further enhance the spectral efficiency. In an
effort to achieve an even more hardware-efficient large antenna array, we also
investigate the design of hybrid beamformers with one-bit resolution (binary)
PSs, and present a novel binary analog precoder and combiner optimization
algorithm with quadratic complexity in the number of antennas. The proposed
low-resolution hybrid beamforming design is further extended to multiuser MIMO
communication systems. Simulation results demonstrate the performance
advantages of the proposed algorithms compared to existing low-resolution
hybrid beamforming designs, particularly for the one-bit resolution PS
scenario
Bat algorithm–based beamforming for mmWave massive MIMO systems
© 2019 John Wiley & Sons, Ltd. In this paper, an optimized analog beamforming scheme for millimeter-wave (mmWave) massive MIMO system is presented. This scheme aims to achieve the near-optimal performance.by searching for the optimized combination of analog precoder and combiner. In order to compensate for the occurrence of attenuation in the magnitude of mmWave signals, the codebook-dependent analog beamforming in conjunction with precoding at transmitting end and combining signals at the receiving end is utilized. Nonetheless, the existing and traditional beamforming schemes involve a more difficult and complicated search for the optimal combination of analog precoder/combiner matrices from predefined codebooks. To solve this problem, we have referred to a modified bat algorithm to find the optimal combination value. This algorithm will explore the possible pairs of analog precoder/combiner as a way to come up with the best match in order to attain near-optimal performance. The analysis shows that the optimized beamforming scheme presented in this paper can improve the performance that is very close to the beam steering benchmark that we have considered.Published versio
A Comparison of Beam Refinement Algorithms for Millimeter Wave Initial Access
Initial access (IA) is identified as a key challenge for the upcoming 5G mobile communication system operating at high carrier frequencies, and several techniques are currently being proposed. In this paper, we extend our previously proposed genetic algorithm (GA)-based beam refinement scheme to include beamforming at both the transmitter and the receiver, and compare the performance with alternative approaches in the millimeter wave multi-user multiple-input-multiple-output (MU-MIMO) networks. Taking the millimeter wave communications characteristics and various metrics into account, we investigate the effect of different parameters such as the number of transmit antennas/users/per-user receive antennas, beamforming resolution as well as hardware impairments on the system performance employing different beam refinement algorithms. As shown, our proposed GA-based approach performs well in delay-constrained networks with multi-antenna users. Compared to the considered state-of-the-art schemes, our method reaches the highest service outage-constrained end-to-end throughput with considerably less implementation complexity. Moreover, taking the users\u27 mobility into account, GA-based approach can remarkably reduce the beam refinement delay at low/moderate speeds when the spatial correlation is taken into account
Genetic Algorithm-Based Beam Refinement for Initial Access in Millimeter Wave Mobile Networks
Initial access (IA) is identified as a key challenge for the upcoming 5G mobile communication system operating at high carrier frequencies, and several techniques are currently being proposed. In this paper, we extend our previously proposed efficient genetic algorithm-(GA-) based beam refinement scheme to include beamforming at both the transmitter and the receiver and compare the performance with alternative approaches in the millimeter wave multiuser multiple-input-multiple-output (MU-MIMO) networks. Taking the millimeter wave communications characteristics and various metrics into account, we investigate the effect of different parameters such as the number of transmit antennas/users/per-user receive antennas, beamforming resolutions, and hardware impairments on the system performance employing different beam refinement algorithms. As shown, our proposed GA-based approach performs well in delay-constrained networks with multiantenna users. Compared to the considered state-of-the-art schemes, our method reaches the highest service outage-constrained end-to-end throughput with considerably less implementation complexity. Moreover, taking the users\u27 mobility into account, our GA-based approach can remarkably reduce the beam refinement delay at low/moderate speeds when the spatial correlation is taken into account. Finally, we compare the cases of collaborative users and noncollaborative users and evaluate their difference in system performance