scispace - formally typeset
Journal ArticleDOI

Hybrid Analog-Digital Transceiver Designs for Multi-User MIMO mmWave Cognitive Radio Systems

Reads0
Chats0
TLDR
Simulations show that the performance of the proposed hybrid A/D approaches is very close to the one of the corresponding fully digital transceivers for typical experimental setups.
Abstract
Millimeter wave (mmWave) band mobile communications can be a solution to the continuously increasing traffic demand in modern wireless systems. Even though mmWave bands are scarcely occupied, the design of a prospect transceiver should guarantee the efficient coexistence with the incumbent services in these bands. To that end, in this paper, multi-user underlay cognitive transceiver designs are proposed that enable the mmWave spectrum access while controlling the interference to the incumbent users. MmWave systems usually require large-scale antenna arrays to achieve satisfactory performance and thus, it is difficult to support fully digital transceiver designs due to high demands in hardware complexity and power consumption. Thus, in order to develop efficient solutions, the proposed approaches are based on a hybrid analog-digital (A/D) architecture. Transceiver designs are developed for both the uplink and the downlink regime of a multi-user cellular system. Efficient algorithmic solutions are proposed for the design of the analog and the digital counterparts of the precoding and the decoding matrices of the latter systems based on the Alternating Direction Method of Multipliers (ADMM). Simulations show that the performance of the proposed hybrid A/D approaches is very close to the one of the corresponding fully digital transceivers for typical experimental setups.

read more

Citations
More filters
Journal ArticleDOI

A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks

TL;DR: In this paper, the authors shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing and energy, from its core to its end nodes.

Millimeter wave beamforming for wireless backhaul and access in small cell networks and practical approaches in software-defined radio

TL;DR: In this paper, an efficient beam alignment technique using adaptive subspace sampling and hierarchical beam codebooks was proposed to solve the problem of spectrum reusability and flexible prototyping radio platform using software-defined radio (SDR).
Journal ArticleDOI

Learn to Schedule (LEASCH): A Deep Reinforcement Learning Approach for Radio Resource Scheduling in the 5G MAC Layer

TL;DR: LEASCH is a deep reinforcement learning model able to solve the radio resource scheduling problem in the MAC layer of 5G networks and is both numerology-agnostic and efficient when compared to conventional baseline methods in many key performance indicators.
Journal ArticleDOI

Hybrid Beamforming, User Scheduling, and Resource Allocation for Integrated Terrestrial-Satellite Communication

TL;DR: In this paper, a hybrid beamforming, user scheduling, and resource allocation optimization based on spectrum coexisting forward transmission in integrated terrestrial-satellite network (ITSN) with the purpose of improving system sum rate and energy efficiency is investigated.
Posted Content

Joint Bit Allocation and Hybrid Beamforming Optimization for Energy Efficient Millimeter Wave MIMO Systems

TL;DR: A novel and efficient solution based on the alternating direction method of multipliers is proposed to solve these problems at both the TX and the RX, and achieves higher energy efficiency when compared with existing benchmark techniques that use fixed DAC/ADC bit resolutions.
References
More filters
Book

Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers

TL;DR: It is argued that the alternating direction method of multipliers is well suited to distributed convex optimization, and in particular to large-scale problems arising in statistics, machine learning, and related areas.
Journal ArticleDOI

Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!

TL;DR: The motivation for new mm-wave cellular systems, methodology, and hardware for measurements are presented and a variety of measurement results are offered that show 28 and 38 GHz frequencies can be used when employing steerable directional antennas at base stations and mobile devices.
Journal ArticleDOI

Spatially Sparse Precoding in Millimeter Wave MIMO Systems

TL;DR: This paper considers transmit precoding and receiver combining in mmWave systems with large antenna arrays and develops algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware.
Journal ArticleDOI

On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators

TL;DR: This paper shows, by means of an operator called asplitting operator, that the Douglas—Rachford splitting method for finding a zero of the sum of two monotone operators is a special case of the proximal point algorithm, which allows the unification and generalization of a variety of convex programming algorithms.
Journal ArticleDOI

Breaking Spectrum Gridlock With Cognitive Radios: An Information Theoretic Perspective

TL;DR: This information-theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today's crowded spectrum.
Related Papers (5)