69 research outputs found
Handling Interference in Integrated HAPS-Terrestrial Networks through Radio Resource Management
Vertical heterogeneous networks (vHetNets) are promising architectures to
bring significant advantages for 6G and beyond mobile communications. High
altitude platform station (HAPS), one of the nodes in the vHetNets, can be
considered as a complementary platform for terrestrial networks to meet the
ever-increasing dynamic capacity demand and provide sustainable wireless
networks for future. However, the problem of interference is the bottleneck for
the optimal operation of such an integrated network. Thus, designing efficient
interference management techniques is inevitable. In this work, we aim to
design a joint power-subcarrier allocation scheme in order to achieve fairness
for all users. We formulate the max-min fairness (MMF) optimization problem and
develop a rapid converging iterative algorithm to solve it. Numerical results
validate the superiority of the proposed algorithm and show better performance
over other conventional network scenarios.Comment: 7 pages, 3 figures, Accepted by IEEE Wireless Communications Letter
Erlang analysis of cellular networks using stochastic Petri nets and user-in-the-loop extension for demand control
AbstractâCellular networks face severe challenges due to the expected growth of application data rate demand with an increase rate of 100 % per year. Over-provisioning capacity has been the standard approach to reduce the risk of overload situations. Traditionally in telephony networks, call blocking and overload probability have been analyzed using the Erlang-B and Erlang-C formulas, which model limited capacity communication systems without or with session request buffers, respectively. While a closed-form expression exists for the blocking probability for constant load and service, a steady-state Markov chain (MC) analysis can always provide more detailed data, as long as the Markov property of the arrival and service processes hold. However, there is a significant modeling advantage by using the stochastic Petri net (SPN) paradigm to model the details of such a system. In addition, software tool support allows getting numeric analysis results quickly by solving the state probabilities in the background and without the need to run any simulation. Because of this efficiency, the equivalent SPN model of the Engset, Erlang-B and Erlang-C situation is introduced as novelty in this paper. Going beyond the original Erlang scenario, the user-in-the-loop (UIL) approach of demand shaping by closed-loop control is studied as an extension. In UIL, demand control is implemented by a dynamic usage-based tariff which motivates users to reduce or postpone the use of applications on their smart phone in times of light to severe congestion. In this paper, the effect of load on the price and demand reduction is modeled with an SPN based on the classical Erlang Markov chain structure. Numeric results are easily obtained and presented in this paper, including probability density functions (PDF) of the load situation, and a parameter analysis showing the effectiveness of UIL to reduce the overload probability. KeywordsâUser-in-the-loop (UIL); demand shaping; demand control; congestion; Erlang; stochastic Petri-net (SPN). I
Provisioning quality-of-service to energy harvesting wireless communications
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Energy harvesting (EH) is an innovative way to build long-term and self-sustainable wireless networks. However, an inconstant EH rate may have an adverse effect on the quality-of-service (QoS) of wireless traffic, such as packet delay and error. In this article we discuss techniques that provide QoS to EH powered wireless communications. A new "dynamic string tautening" method is presented to produce the most energy efficient schedule with substantially lower complexity, compared to convex optimization techniques. The method adapts to the bursty arrivals of wireless traffic and harvested energy, and ensures that delay-sensitive data will be delivered by deadline. Comprehensive designs of EH powered transmitters are also discussed, where the EH rate, battery capacity, and deadline requirement can be jointly adjusted to leverage QoS and the cost.Peer reviewe
Energy-Efficient Wireless Communications with Distributed Reconfigurable Intelligent Surfaces
This paper investigates the problem of resource allocation for a wireless
communication network with distributed reconfigurable intelligent surfaces
(RISs). In this network, multiple RISs are spatially distributed to serve
wireless users and the energy efficiency of the network is maximized by
dynamically controlling the on-off status of each RIS as well as optimizing the
reflection coefficients matrix of the RISs. This problem is posed as a joint
optimization problem of transmit beamforming and RIS control, whose goal is to
maximize the energy efficiency under minimum rate constraints of the users. To
solve this problem, two iterative algorithms are proposed for the single-user
case and multi-user case. For the single-user case, the phase optimization
problem is solved by using a successive convex approximation method, which
admits a closed-form solution at each step. Moreover, the optimal RIS on-off
status is obtained by using the dual method. For the multi-user case, a
low-complexity greedy searching method is proposed to solve the RIS on-off
optimization problem. Simulation results show that the proposed scheme achieves
up to 33\% and 68\% gains in terms of the energy efficiency in both single-user
and multi-user cases compared to the conventional RIS scheme and
amplify-and-forward relay scheme, respectively
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