Spatial Transmitter Density Allocation for Frequency-Selective Wireless Ad Hoc Networks

Wang, Zhengdao

doi:10.1109/twc.2018.2881707

Cited by 8 publications

(10 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, from Equations (14) and (39), the overall optimal throughput of the SNO-CRAVNET system amongst all the R CRV-SUs and subcarriers can be obtained, for instance,…”

Section: Theoremmentioning

confidence: 99%

“…By applying the properties of the Lambert-Ⱳ function [38,39] Based on Equation 35, the matrix ℂ ×ℝ * ×ℝ = ℂ * , which illustrates the time-sharing scheduling of each subcarrier for all the ℝ CRV-SUs, is determined. Additionally, this further helps in determining the quality of each subcarrier, that is, based on Equation 35, if it is observed that ℂ * < ℂ * , this indicates that even though both subcarriers were allocated an equal amount of transmit power, subcarrier requires less time than subcarrier for the transfer of an equal amount of information by the same CRV-SU .…”

Section: (A12)mentioning

confidence: 99%

“…However, recursive numerical methods are known to be computati intensive [36,37] . By applying the properties of the Lambert-Ⱳ function [38,39] . Therefore, by relating Equations (A7) and (A14), the optimal transmit power allocation the proposed novel SNO-CRAVNET is determined to in Equation (36).…”

Section: (A12)mentioning

confidence: 99%

See 2 more Smart Citations

Design Optimization of Resource Allocation in OFDMA-based Cognitive Radio-enabled Internet of Vehicles (IoVs)

Eze

Zhang

et al. 2019

2019 25th International Conference on Automation and Computing (ICAC)

View full text Add to dashboard Cite

Joint optimal subcarrier and transmit power allocation with QoS guarantee for enhanced packet transmission over Cognitive Radio (CR)-Internet of Vehicles (IoVs) is a challenge. This open issue is considered in this paper. A novel SNBS-based wireless radio resource scheduling scheme in OFDMA CR-IoV network systems is proposed. This novel scheduler is termed the SNBS OFDMA-based overlay CR-Assisted Vehicular NETwork (SNO-CRAVNET) scheduling scheme. It is proposed for efficient joint transmit power and subcarrier allocation for dynamic spectral resource access in cellular OFDMA-based overlay CRAVNs in clusters. The objectives of the optimization model applied in this study include (1) maximization of the overall system throughput of the CR-IoV system, (2) avoiding harmful interference of transmissions of the shared channels' licensed owners (or primary users (PUs)), (3) guaranteeing the proportional fairness and minimum data-rate requirement of each CR vehicular secondary user (CRV-SU), and (4) ensuring efficient transmit power allocation amongst CRV-SUs. Furthermore, a novel approach which uses Lambert-W function characteristics is introduced. Closed-form analytical solutions were obtained by applying time-sharing variable transformation. Finally, a low-complexity algorithm was developed. This algorithm overcame the iterative processes associated with searching for the optimal solution numerically through iterative programming methods. Theoretical analysis and simulation results demonstrated that, under similar conditions, the proposed solutions outperformed the reference scheduler schemes. In comparison to other scheduling schemes that are fairness-considerate, the SNO-CRAVNET scheme achieved a significantly higher overall average throughput gain. Similarly, the proposed time-sharing SNO-CRAVNET allocation based on the reformulated convex optimization problem is shown to be capable of achieving up to 99.987% for the average of the total theoretical capacity.

show abstract

“…Therefore, from Equations (14) and (39), the overall optimal throughput of the SNO-CRAVNET system amongst all the R CRV-SUs and subcarriers can be obtained, for instance,…”

Section: Theoremmentioning

confidence: 99%

Section: (A12)mentioning

confidence: 99%

See 1 more Smart Citation

Design Optimization of Resource Allocation in OFDMA-based Cognitive Radio-enabled Internet of Vehicles (IoVs)

Eze

Zhang

et al. 2019

2019 25th International Conference on Automation and Computing (ICAC)

View full text Add to dashboard Cite

show abstract

“…In [5], for two heterogeneous networks coexisting together, a comparison between spectrum sharing and spectrum splitting is studied in terms of the average spectral efficiency. A recent work [6] focuses on BWP for frequency-selective channels with an aim to maximize the total density of concurrent transmissions subject to the outage constraint at the typical link. In [7], the density of reliable transmissions is maximized for ALOHA-based uncoordinated wireless networks without BWP.…”

Section: Related Workmentioning

confidence: 99%

Reliability and Local Delay in Wireless Networks: Does Bandwidth Partitioning Help?

Kalamkar

2019

2019 IEEE Global Communications Conference (GLOBECOM)

View full text Add to dashboard Cite

This paper studies the effect of bandwidth partitioning (BWP) on the reliability and delay performance in infrastructureless wireless networks. The reliability performance is characterized by the density of concurrent transmissions that satisfy a certain reliability (outage) constraint and the delay performance by so-called local delay, defined as the average number of time slots required to successfully transmit a packet. We concentrate on the ultrareliable regime where the target outage probability is close to 0. BWP has two conflicting effects: while the interference is reduced as the concurrent transmissions are divided over multiple frequency bands, the signal-to-interference ratio (SIR) requirement is increased due to smaller allocated bandwidth if the data rate is to be kept constant. Instead, if the SIR requirement is to be kept the same, BWP reduces the data rate and in turn increases the local delay. For these two approaches with adaptive and fixed SIR requirements, we derive closed-form expressions of the local delay and the maximum density of reliable transmissions in the ultrareliable regime. Our analysis shows that, in the ultrareliable regime, BWP leads to the reliability-delay tradeoff.

show abstract

“…For other setups, similar min-max problems can be formulated, some of which can be solved optimally (e.g., power control [15]- [17], transmitter density allocation [18], or certain MISO beamforing [19], [20]). But for general multi-channel and/or MIMO interference channel, the corresponding problem is NP-hard [21].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications

Tsaknakis

Mei

et al. 2020

IEEE Trans. Signal Process.

Self Cite

View full text Add to dashboard Cite

The min-max problem, also known as the saddle point problem, is a class of optimization problems in which we minimize and maximize two subsets of variables simultaneously. This class of problems can be used to formulate a wide range of signal processing and communication (SPCOM) problems.Despite its popularity, existing theory for this class has been mainly developed for problems with certain special convex-concave structure. Therefore, it cannot be used to guide the algorithm design for many interesting problems in SPCOM, where some kind of non-convexity often arises.In this work, we consider a general block-wise one-sided non-convex min-max problem, in which the minimization problem consists of multiple blocks and is non-convex, while the maximization problem is (strongly) concave. We propose a class of simple algorithms named Hybrid Block Successive Approximation (HiBSA), which alternatingly performs gradient descent-type steps for the minimization blocks and one gradient ascent-type step for the maximization problem. A key element in the proposed algorithm is the introduction of certain properly designed regularization and penalty terms, which are used to stabilize the algorithm and ensure convergence. For the first time, we show that such simple alternating min-max algorithms converge to first-order stationary solutions, with quantifiable global rates. To validate the efficiency of the proposed algorithms, we conduct numerical tests on a number of information processing and wireless communication problems, including the robust learning problem, the non-convex min-utility maximization problems, and certain wireless jamming problem arising in interfering channels. * The first two authors contributed equally to this work, and the names are listed alphabetically. S. Lu, I. Tsaknakis and M. Hong are with the DRAFT Problem (1) is quite generic, and it arises in a wide range of signal processing and communication (SPCOM) applications. We list of few of these applications below. A. Motivating Examples in SPCOMDistributed non-convex optimization: Consider a network of K agents defined by a connected graph G = {V, E} with |V| = K, where each agent i can communicate with its neighbors. A generic problem formulation that captures many problems that appear in distributed machine learning and signal processing (e.g., [2]-[5]) can be formulated as follows:

show abstract

Spatial Transmitter Density Allocation for Frequency-Selective Wireless Ad Hoc Networks

Cited by 8 publications

References 41 publications

Design Optimization of Resource Allocation in OFDMA-based Cognitive Radio-enabled Internet of Vehicles (IoVs)

Design Optimization of Resource Allocation in OFDMA-based Cognitive Radio-enabled Internet of Vehicles (IoVs)

Reliability and Local Delay in Wireless Networks: Does Bandwidth Partitioning Help?

Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications

Contact Info

Product

Resources

About