- Cooperative Spectrum Sensing in Cognitive Radio Networks with QoS Requirements | SpringerLink.
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Qixuan Zhu and Xi Zhang. Xi Zhang and Fan Yang.
Xi Zhang and Jingqing Wang. Xi Zhang and Qixuan Zhu. Please report errors in award information by writing to: awardsearch nsf. Search Awards. Recent Awards. Presidential and Honorary Awards. About Awards.
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How to Manage Your Award. Grant Policy Manual. Grant General Conditions. Cooperative Agreement Conditions. Special Conditions. Federal Demonstration Partnership. Policy Office Website. Xi Zhang xizhang ece. College Station, TX Program Reference Code s :. In addition, we investigate the impact of having a full-duplex capability at the SU on the network performance, compared to the case of a half-duplex SU.
We consider a cooperative cognitive radio CR network with multipacket reception MPR capabilities at the receiving nodes.
Power Control and Resource Allocation for QoS-Constrained Wireless Networks
In our proposed system, the SU not only exploits the idle time slots i. The resultant optimization problem turns out to be a non-convex quadratic constrained quadratic programming QCQP optimization problem, which is, in general, an NP-hard problem. An efficient approach is devised to solve it and characterize the stability region of the network under a delay constraint on the PU.
Numerical results, surprisingly, reveal that the network performance with a full-duplex SU is not always better than that of a half-duplex SU. In fact, we show that a full-duplex capability at the SU can adversely affect the stability performance of the network especially if the channel condition between the SU and the destinations is weaker than that between the PU and the destinations. Rizk, Mohamed Salman, Karim G. In this paper we present the dependency between density of sensor network and map quality in the Radio Environment Map REM concept.
The architecture of REM supporting military communications systems is described. The map construction techniques based on spatial statistics and transmitter location determination are presented. The problem of REM quality and relevant metrics are discussed. The results of field tests for UHF range with different number of sensors are shown.
Exemplary REM maps with different interpolation algorithms are presented. Finally, the problem of density of sensors network versus REM map quality is analyzed. Channel-charting CC is a machine learning technique for learning a multi-cell radio map, which can be used for cognitive radio-resource-management RRM problems.
Each base-station BS extracts features from the channel-state-information samples CSI from transmissions of user-equipment UE at different unknown locations. The multi-path channel components are estimated and used to construct a dissimilarity matrix between CSI samples at each BS. A fusion center combines the dissimilarity matrices of all base-stations, performs dimensional reduction based on manifold learning, constructing a Multipoint-CC MPCC. The MPCC is a two dimension map, where the spatial difference between any pair of UEs closely approximates the distance between the clustered features.
Simulation results are used to show the merits of the proposed approach. This work introduces a spectrum-agile wideband autonomous cognitive radio WACR that is capable of avoiding interference and jamming signals. Moreover, it introduces new definitions for the state and the operation parameters that enable the WACR to collect information about the RF spectrum of interest in both time and frequency domains.
The simulation results show that the proposed technique can efficiently learn an effective strategy to avoid harmful signals in a wideband partially observable environment. Furthermore, the experiments on an over-the-air channel inside a laboratory show that the proposed algorithm can rapidly adapt to sudden changes in the surrounding RF environment making it suitable for real-time applications. Localization techniques are going to be a significant part of 5G networks, not only for user-plane services e.
This paper firstly, provides comprehensive overview of the existing localization techniques that can be used in 5G systems focusing on cellular network-based solutions and advancement in satellite-based localization. Secondly, these techniques are analysed and assessed against the requirements stated for 5G REM systems. Since the main feature of Named Data Network NDN is in-net caching, it is crucial to motivate users to offer resource such as bandwidth and storage. However, few research works on incentive mechanism design for NDN. Since blockchain can supply a traceable and credible environment while public chain has long latency and low throughput, the paper combines permissioned chain with public chain, constructs a hybrid chain based environment without hurting its truthfulness.
Furthermore, the paper formulates the market as a reverse auction running by a Content Provider CP who aims to serve more users for profit by leasing resource from APs, and investigates incentive mechanism for motivating APs. Especially, the paper designs an optimal mechanism, which could overcome defects of traditional mechanism, get the most profit for CP with guaranteeing interest of AP. Evaluation results compare effectiveness of mechanism proposed with traditional incentive mechanism, and prove that the mechanism we designed could get better results.
Therefore, the major challenge in designing the 5G networks is how to support different types of users and applications with different quality-of-service requirements under a single physical network infrastructure. We propose an efficient RAN slicing scheme based on offline reinforcement learning that allocates radio resources to different slices while accounting for their utility requirements and the dynamic changes in the traffic load in order to maximize efficiency of the resource utilization.
A simulation-based analysis is presented to assess the performance of the proposed solution. Ubiquitous connectivity is one of the foundational technologies enabling data sharing amongst participating components of an industrial internet of things IIoT system. The growing pressure to open the mobile market for location specific networks has resulted in new regional licensing and sharing-based models for spectrum access, to allow the emergence of local networks to serve different verticals. While the development of technical solutions for network performance is progressing, less attention has been paid to the spectrum management approaches for the new industrial networks and location specific service offerings.
This paper examines solutions to problems currently faced by industry in acquiring spectrum to support the IIoT along with introducing a framework that should be accounted for when assessing the feasibility of the spectrum management approaches. The key question that we address is whether and to which extent the MNO has incentive to adopt this form of QoS-aware pricing. The second step is to compute the maximum revenue of the MNO.
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Our analysis reveals that the MNO can always tune the prices so as to maximise its revenue for the scenario where all users belong to the high QoS class. This is a consistent result throughout our study, that holds for any considered set of user-controlled parameters and of technical parameters.
Emerging private LTE and 5G services and applications have created need for local radio spectrum licensing. The existing pricing models for licenses do not work well in this context. This paper introduces three new location dependent valuation methods that aim to produce more accurate pricing for local licenses. We use FICORA Frequency Fee as our base-case general spectrum valuation model, and we replace the population density based location coefficient with proxies such as employee density, value added per employee, and rent prices.
By comparing the differences in the prices yielded by the models, we show that the new models can in some cases identify high demand areas like hospitals and industrial districts better than the original population density based model. Additionally, we conclude that the original population density based model and the new employee density based model could be used together to capture both the consumer and the industrial spectrum demand simultaneously. Therefore point-to-multipoint is considered to be an essential feature for many 5G applications.
Different 5G applications differ greatly in terms of coverage, bit rate and quality of service they require. This study analyses the spectrum allocation options for each use case in different spectrum bands and with different spectrum allocation methods, ranging from exclusive licensing to spectrum sharing and unlicensed spectrum.
Services on Demand
The different analyses map use cases to spectrum bands, spectrum bands to allocation options, use cases to allocation options, and all these are brought together in use case - spectrum band - allocation option - operator mapping. To reduce the transmission energy and latency when servicing the users who are interested in a common popular content, the base station BS chooses to deliver the content to the users nearby with less power.
To find a low complexity computational solution to the problem, we first propose an algorithm to select the RUEs based on the set criteria, and then a coalition formation game based algorithm is proposed for the DUEs association. We further prove that the proposed algorithm is convergent. Numerical results demonstrate that the algorithms we proposed yield notable gains compare with short-term optimal scheme and non-cooperative scheme. While the development of technical solutions for network densification is progressing, less attention is paid to the spectrum models for the new ultra-dense networks and location specific service offerings.
Industrial applications where such spectrum is needed were assessed and their requirements identified. This study developed a view of options for the spectrum supply side, how this could interface with demand from private networks. The leasing rules defined for CBRS PALs also provides an excellent minimal overhead option for enterprises to lease spectrum to other neighboring enterprises.
Furthermore, the CBRS concept was found to leverage all the three forces of the long tail framework: Democratizing the tools of production through access to affordable spectrum, cutting the costs of consumption by democratizing distribution with web-scale automatization and connecting supply and demand via marketplace via SAS. Web based thin clients are applications delivering content from the Internet or Intranet and accessed via the browser on the running end device.
These clients are portable and cross-device compatible and have a large spectrum of applications, can perform from tele-measurement tasks to management and information centralization. The capability of web-based thin clients to function offline is a requirement that is indispensable even today for many companies because offline-enabled thin clients allow the users to continue working without workflow disturbance, preventing the loss of data, even when the connection to the Internet is missing or malfunctioning.
The main challenge of supporting Internet of Things IoT in 5G network is to provide massive connectivity to machine-type communication devices MTCDs , with sporadic small-size data transmission. Narrowband technology is energyefficient with extended coverage, on a narrow bandwidth, for low-rate and low-cost MTCDs. Grant-free transmission is expected to support random uplink communication, however, this distributed manner leads to high collision probability.
Nonorthogonal multiple access NOMA can be used in grantfree transmission, which multiplies connection opportunities by exploiting power domain. However, coordinated NOMA schemes where base station performs coordination is not suitable for grant-free transmissions.
In this paper, based on a detailed analysis of the novel distributed grant-free NOMA scheme proposed in our previous work, a stabilized distributed narrow-band NOMA scheme is proposed to reduce collision probability, which derives the optimal re transmission probability for each MTCD. With the stabilized scheme, the system can be always stable and its throughput can be guaranteed whatever the new arrival rate is. Simulation results reveal that, when the system is overloaded, for uplink throughput, our proposed scheme outperforms by This paper presents the 5G CrowdCell platform developed by Lime Microsystems, as well as future mm-Wave SDR platforms which are under development, and which, among other applications, will be used as the CrowdCell backhaul.
The Fifth Generation 5G mobile communication standard is expected to come on-line in Among the performance requirements of 5G, stands out the capacity, that is expected to be fold of the Fourth Generation 4G. Several technologies have been considered to achieve this goal, among them Full Duplex communications.