82 research outputs found
Cross-layer design for single-cell OFDMA systems with heterogeneous QoS and partial CSIT
Abstractâ This paper proposes a novel cross-layer scheduling scheme for a single-cell orthogonal frequency division multiple access (OFDMA) wireless system with partial channel state information (CSI) at transmitter (CSIT) and heterogeneous user delay requirements. Previous research efforts on OFDMA resource allocation are typically based on the availability of perfect CSI or imperfect CSI but with small error variance. Either case consists to typify a non tangible system as the potential facts of channel feedback delay or large channel estimation errors have not been considered. Thus, to attain a more realistic resolution our cross-layer design determines optimal subcarrier and power allocation policies based on partial CSIT and individual userâs quality of service (QoS) requirements. The simulation results show that the proposed cross-layer scheduler can maximize the systemâs throughput and at the same time satisfy heterogeneous delay requirements of various users with significant low power consumption
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Cross-layer design for OFDMA wireless networks with finite queue length based on game theory
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.In next generation wireless networks such as 4G- LTE and WiMax, the demand for high data rates, the scarcity of wireless resources and the time varying channel conditions has led to the adoption of more sophisticated and robust techniques in PHY such as orthogonal frequency division multiplexing (OFDM) and the corresponding access technique known as orthogonal frequency division multiplexing access (OFDMA). Cross-layer schedulers have been developed in order to describe the procedure of resource allocation in OFDMA wireless networks. The resource allocation in OFDMA wireless networks has received great attention in research, by proposing many different ways for frequency diversity exploitation and systemâs optimization. Many cross-layer proposals for dynamic resource allocation have been investigated in literature approaching the optimization problem from different viewpoints i.e. maximizing total data rate, minimizing total transmit power, satisfying minimum usersâ requirements or providing fairness amongst users. The design of a cross-layer scheduler for OFDMA wireless networks is the topic of this research. The scheduler utilizes game theory in order to make decisions for subcarrier and power allocation to the users with the main concern being to maintain fairness as well as to maximize overall systemâs performance. A very well known theorem in cooperative game theory, the Nash Bargaining Solution (NBS), is employed and solved in a close form way, resulting in a Pareto optimal solution. Two different cases are proposed. The first one is the symmetric NBS (S-NBS) where all users have the same weight and therefore all users have the same opportunity for resources and the second one, is the asymmetric NBS (A-NBS), where users have different weights, hence different priorities where the scheduler favours users with higher priorities at expense of lower priority users. As MAC layer is vital for cross-layer, the scheduler is combined with a queuing model based on Markov chain in order to describe more realistically the incoming procedure from the higher layers
Rate-Splitting Multiple Access for 6G -- Part I: Principles, Applications and Future Works
This letter is the first part of a three-part tutorial focusing on
rate-splitting multiple access (RSMA) for 6G. As Part I of the tutorial, the
letter presents the basics of RSMA and its applications in light of 6G. To
begin with, we first delineate the design principle and basic transmission
frameworks of downlink and uplink RSMA. We then illustrate the applications of
RSMA for addressing the challenges of various potential enabling technologies
and use cases, consequently making it a promising next generation multiple
access (NGMA) scheme for future networks such as 6G and beyond. We briefly
discuss the challenges of RSMA and conclude the letter. In continuation of Part
I, we will focus on the interplay of RSMA with integrated sensing and
communication, and reconfigurable intelligent surfaces, respectively in Part II
and Part III of this tutorial
Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolution
MIMO processing plays a central part towards the recent increase in spectral
and energy efficiencies of wireless networks. MIMO has grown beyond the
original point-to-point channel and nowadays refers to a diverse range of
centralized and distributed deployments. The fundamental bottleneck towards
enormous spectral and energy efficiency benefits in multiuser MIMO networks
lies in a huge demand for accurate channel state information at the transmitter
(CSIT). This has become increasingly difficult to satisfy due to the increasing
number of antennas and access points in next generation wireless networks
relying on dense heterogeneous networks and transmitters equipped with a large
number of antennas. CSIT inaccuracy results in a multi-user interference
problem that is the primary bottleneck of MIMO wireless networks. Looking
backward, the problem has been to strive to apply techniques designed for
perfect CSIT to scenarios with imperfect CSIT. In this paper, we depart from
this conventional approach and introduce the readers to a promising strategy
based on rate-splitting. Rate-splitting relies on the transmission of common
and private messages and is shown to provide significant benefits in terms of
spectral and energy efficiencies, reliability and CSI feedback overhead
reduction over conventional strategies used in LTE-A and exclusively relying on
private message transmissions. Open problems, impact on standard specifications
and operational challenges are also discussed.Comment: accepted to IEEE Communication Magazine, special issue on LTE
Evolutio
Two-Stage Subspace Constrained Precoding in Massive MIMO Cellular Systems
We propose a subspace constrained precoding scheme that exploits the spatial
channel correlation structure in massive MIMO cellular systems to fully unleash
the tremendous gain provided by massive antenna array with reduced channel
state information (CSI) signaling overhead. The MIMO precoder at each base
station (BS) is partitioned into an inner precoder and a Transmit (Tx) subspace
control matrix. The inner precoder is adaptive to the local CSI at each BS for
spatial multiplexing gain. The Tx subspace control is adaptive to the channel
statistics for inter-cell interference mitigation and Quality of Service (QoS)
optimization. Specifically, the Tx subspace control is formulated as a QoS
optimization problem which involves an SINR chance constraint where the
probability of each user's SINR not satisfying a service requirement must not
exceed a given outage probability. Such chance constraint cannot be handled by
the existing methods due to the two stage precoding structure. To tackle this,
we propose a bi-convex approximation approach, which consists of three key
ingredients: random matrix theory, chance constrained optimization and
semidefinite relaxation. Then we propose an efficient algorithm to find the
optimal solution of the resulting bi-convex approximation problem. Simulations
show that the proposed design has significant gain over various baselines.Comment: 13 pages, accepted by IEEE Transactions on Wireless Communication
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