809 research outputs found
Interference Exploitation-based Hybrid Precoding with Robustness Against Phase Errors
Hybrid analog-digital precoding significantly reduces the hardware costs in
massive MIMO transceivers when compared to fully-digital precoding at the
expense of increased transmit power. In order to mitigate the above shortfall,
we use the concept of constructive interference-based precoding, which has been
shown to offer significant transmit power savings when compared with the
conventional interference suppression-based precoding in fully-digital
multiuser MIMO systems. Moreover, in order to circumvent the potential
quality-of-service degradation at the users due to the hardware impairments in
the transmitters, we judiciously incorporate robustness against such
vulnerabilities in the precoder design. Since the undertaken constructive
interference-based robust hybrid precoding problem is nonconvex with infinite
constraints and thus difficult to solve optimally, we decompose the problem
into two subtasks, namely, analog precoding and digital precoding. In this
paper, we propose an algorithm to compute the optimal constructive
interference-based robust digital precoders. Furthermore, we devise a scheme to
facilitate the implementation of the proposed algorithm in a low-complexity and
distributed manner. We also discuss block-level analog precoding techniques.
Simulation results demonstrate the superiority of the proposed algorithm and
its implementation scheme over the state-of-the-art methods
Codebook Based Hybrid Precoding for Millimeter Wave Multiuser Systems
In millimeter wave (mmWave) systems, antenna architecture limitations make it
difficult to apply conventional fully digital precoding techniques but call for
low cost analog radio-frequency (RF) and digital baseband hybrid precoding
methods. This paper investigates joint RF-baseband hybrid precoding for the
downlink of multiuser multi-antenna mmWave systems with a limited number of RF
chains. Two performance measures, maximizing the spectral efficiency and the
energy efficiency of the system, are considered. We propose a codebook based RF
precoding design and obtain the channel state information via a beam sweep
procedure. Via the codebook based design, the original system is transformed
into a virtual multiuser downlink system with the RF chain constraint.
Consequently, we are able to simplify the complicated hybrid precoding
optimization problems to joint codeword selection and precoder design (JWSPD)
problems. Then, we propose efficient methods to address the JWSPD problems and
jointly optimize the RF and baseband precoders under the two performance
measures. Finally, extensive numerical results are provided to validate the
effectiveness of the proposed hybrid precoders.Comment: 35 pages, 9 figures, to appear in Trans. on Signal Process, 201
On the Throughput of Large-but-Finite MIMO Networks using Schedulers
This paper studies the sum throughput of the {multi-user}
multiple-input-single-output (MISO) networks in the cases with large but finite
number of transmit antennas and users. Considering continuous and bursty
communication scenarios with different users' data request probabilities, we
derive quasi-closed-form expressions for the maximum achievable throughput of
the networks using optimal schedulers. The results are obtained in various
cases with different levels of interference cancellation. Also, we develop an
efficient scheduling scheme using genetic algorithms (GAs), and evaluate the
effect of different parameters, such as channel/precoding models, number of
antennas/users, scheduling costs and power amplifiers' efficiency, on the
system performance. Finally, we use the recent results on the achievable rates
of finite block-length codes to analyze the system performance in the cases
with short packets. As demonstrated, the proposed GA-based scheduler reaches
(almost) the same throughput as in the exhaustive search-based optimal
scheduler, with substantially less implementation complexity. Moreover, the
power amplifiers' inefficiency and the scheduling delay affect the performance
of the scheduling-based systems significantly
Joint Symbol-Level Precoding and Reflecting Designs for IRS-Enhanced MU-MISO Systems
Intelligent reflecting surfaces (IRSs) have emerged as a revolutionary solution to enhance wireless communications by changing propagation environment in a cost-effective and hardware-efficient fashion. In addition, symbol-level precoding (SLP) has attracted considerable attention recently due to its advantages in converting multiuser interference (MUI) into useful signal energy. Therefore, it is of interest to investigate the employment of IRS in symbol-level precoding systems to exploit MUI in a more effective way by manipulating the multiuser channels. In this article, we focus on joint symbol-level precoding and reflecting designs in IRS-enhanced multiuser multiple-input single-output (MU-MISO) systems. Both power minimization and quality-of-service (QoS) balancing problems are considered. In order to solve the joint optimization problems, we develop an efficient iterative algorithm to decompose them into separate symbol-level precoding and block-level reflecting design problems. An efficient gradient-projection-based algorithm is utilized to design the symbol-level precoding and a Riemannian conjugate gradient (RCG)-based algorithm is employed to solve the reflecting design problem. Simulation results demonstrate the significant performance improvement introduced by the IRS and illustrate the effectiveness of our proposed algorithms
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