skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Energy-Efficient Power Allocation in Multi-User mmWave Systems With Rate-Splitting Multiple Access
We propose an energy-efficient power allocation algorithm for the multi-user millimeter-wave (mmWave) rate-splitting multiple access (RSMA) downlink with hybrid precoding and quality of service (QoS) constraints. The proposed scheme is applicable to the physical layer design of future wireless networks, such as the 6G cellular downlink, in which a transmitter equipped with multiple antennas must communicate unicast messages to multiple receivers simultaneously. First, we use a low-complexity design to define the analog and digital precoders in closed form. Second, we define an energy efficiency (EE) maximization problem to jointly optimize the power allocation among streams and the common stream rate allocation among users. We then solve the problem using a combination of Dinkelbach’s algorithm and difference of convex functions (DC) programming methods. Simulation results show that the proposed RSMA scheme offers EE improvements over a comparable space division multiple access (SDMA) power allocation scheme in scenarios with perfect and imperfect channel state information at the transmitter. Lastly, we present extensive numerical experiments that suggest that the computational complexity of the proposed RSMA energy-efficient power allocation algorithm can be reduced using the interior-point method such that the computational efficiency of RSMA is comparable to that of SDMA.  more » « less
Award ID(s):
2034616
PAR ID:
10620941
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
IEEE
Date Published:
ISSN:
2577-2465
ISBN:
979-8-3315-1778-6
Page Range / eLocation ID:
1 to 7
Subject(s) / Keyword(s):
Rate-splitting multiple access (RSMA) millimeter wave (mmWave) communication energy efficiency (EE) power allocation hybrid precoding 6G mobile communication
Format(s):
Medium: X
Location:
Washington, DC, USA
Sponsoring Org:
National Science Foundation
More Like this
  1. ; (, IEEE)
    We investigate the energy efficiency (EE) problem in a downlink multi-user millimeter wave (mmWave) rate-splitting multiple access (RSMA) system and propose an energy-efficient one-layer RSMA hybrid precoder design for K users with quality of service constraints. This scheme is applicable to the design of sustainable sixth generation (6G) cellular networks. To make the problem tractable, the analog and the digital precoder designs are decoupled. First, the analog precoder is designed to maximize the desired signal power of each user while ignoring multi-user interference. Second, the digital precoder is designed to manage multi-user interference according to the EE optimization design criterion. We adopt a successive convex approximation-based algorithm for joint optimization of the digital precoders, power, and common rate allocation. Simulation results show that the proposed RSMA scheme always performs at least as well as a baseline spatial division multiple access (SDMA) hybrid precoding scheme and outperforms it under certain channel conditions. These results suggest that RSMA is suitable as a flexible physical layer design for future 6G mmWave networks. 
    more » « less
  2. ; ; ; ; ; (, 2018 IEEE International Conference on Communications (ICC))
    We study downlink transmission in a multi-band heterogeneous network comprising unmanned aerial vehicle (UAV) small base stations and ground-based dual mode mmWave small cells within the coverage area of a microwave (μW) macro base station. We formulate a two-layer optimization framework to simultaneously find efficient coverage radius for the UAVs and energy efficient radio resource management for the network, subject to minimum quality-of-service (QoS) and maximum transmission power constraints. The outer layer derives an optimal coverage radius/height for each UAV as a function of the maximum allowed path loss. The inner layer formulates an optimization problem to maximize the system energy efficiency (EE), defined as the ratio between the aggregate user data rate delivered by the system and its aggregate energy consumption (downlink transmission and circuit power). We demonstrate that at certain values of the target SINR τ introducing the UAV base stations doubles the EE. We also show that an increase in τ beyond an optimal EE point decreases the EE. 
    more » « less
  3. ; ; (, IEEE)
    Spatial non wide-sense stationarities cause partial visibility regions (VRs), and it is a unique propagation characteristic of emerging extra-large aperture arrays (ELAAs). Thus, classification of VRs is a necessity for accurate estimation of channels and efficient design of VR-aware precoders for ELAAs. In this paper, a deep learning framework is proposed to classify VRs in ELAAs. Our objective is to boost the accuracy of classifying VRs based on the uplink pilots received at the ELAAs. Consequently, we focus on guaranteeing user-fairness in the presence of wholly/partial VRs and improving the achievable rates by adopting VR-aware channel estimation and precoding. We propose a hybrid deep learning architecture comprising one dimensional convolutional neural networks and long-short term memory to classify VRs of each user at the ELAA. To achieve a higher accuracy, we generate a diverse dataset through Monte-Carlo simulations that captures numerous combinations of VRs at the ELAA. A transmit power allocation algorithm is also proposed to achieve a common downlink rate for all users irrespective of the different VRs, and its computational complexity is discussed. A set of numerical results is presented to evaluate the performance of our proposed framework. It is efficient and accurate in classifying VRs. Thus, it can be used to enhance the estimation accuracy of ELAA channels with VRs and thereby to design VR-aware precoders to boost spectral/energy efficiency of the next-generation wireless systems. 
    more » « less
  4. ; (, IEEE Journal of Selected Topics in Signal Processing)
    null (Ed.)
    Wireless charging coupled with computation offloading in edge networks offers a promising solution for realizing power-hungry and computation intensive applications on user devices. We consider a mutil-access edge computing (MEC) system with collocated MEC servers and base-stations/access points (BS/AP) supporting multiple users requesting data computation and wireless charging. We propose an integrated solution for wireless charging with computation offloading to satisfy the largest feasible proportion of requested wireless charging while keeping the total energy consumption at the minimum, subject to the MEC-AP transmit power and latency constraints. We propose a novel nested algorithm to jointly perform data partitioning, time allocation, transmit power control and design the optimal energy beamforming for wireless charging. Our resource allocation scheme offers a minimal energy consumption solution compared to other schemes while also delivering a higher amount of wirelessly transferred charge to the users. Even with data offloading, our proposed solution shows significant charging performance, comparable to the case of charging alone, hence showing the effectiveness of performing partial offloading jointly with wireless charging. 
    more » « less
  5. ; ; ; ; ; ; ; (, IEEE Transactions on Communications)
    Compared with traditional half-duplex wireless systems, the application of emerging full-duplex (FD) technology can potentially double the system capacity theoretically. However, conventional techniques for suppressing self-interference (SI) adopted in FD systems require exceedingly high power consumption and expensive hardware. In this paper, we consider employing an intelligent reflecting surface (IRS) in the proximity of an FD base station (BS) to mitigate SI for simultaneously receiving data from uplink users and transmitting information to downlink users. The objective considered is to maximize the system weighted sum-rate by jointly optimizing the IRS phase shifts, the BS transmit beamformers, and the transmit power of the uplink users. To visualize the role of the IRS in SI cancellation, we first study a simple scenario with one downlink user and one uplink user. To address the formulated non-convex problem, a low-complexity algorithm based on successive convex approximation is proposed. For the more general case considering multiple downlink and uplink users, an efficient alternating optimization algorithm based on element-wise optimization is proposed. Numerical results demonstrate that the FD system with the proposed schemes can achieve a larger gain over the half-duplex system, and the IRS is able to achieve a balance between suppressing SI and providing beamforming gain. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email