1,701 research outputs found
Spectral data for parabolic projective symplectic/orthogonal Higgs bundles
No full text Hitchin [Duke Math. J. 54(1), 91–114 (1987)] introduced a proper morphism from the moduli space of stable G-Higgs bundles [[Formula: see text] and [Formula: see text]] over a curve to a vector space of invariant polynomials, and he described the generic fibers of that morphism. In this paper, we first describe the generic Hitchin fibers for the moduli space of stable parabolic projective symplectic/orthogonal Higgs bundles without fixing the determinant. We also describe the generic fibers when the determinant is trivial. 11Nsciescopu
Picard group of moduli of parabolic Higgs bundles
No full textLet X be a compact Riemann surface of genus g >= 3 and let M-par be the moduli space of semistable parabolic bundles over X. Let M-parH denote the moduli space of semistable parabolic Higgs bundles over X. In this article, we study the Picard group of M-par and M-parH.11Nsciescopu
India and Africa ties: challenges and opportunities
No full textIn this post, Dr Sumit Roy* highlights the thinking and the strategies underlying the growing and controversial economic ties between India and Africa in the context of the latter’s pursuit of globalization.¹ Read more articles in the “Why India-Africa relations matter” blog series
Performance Evaluation of 802.11ax OFDMA through Theoretical Analysis and Simulations
No full textWith the introduction of Orthogonal Frequency Division Multiple Access (OFDMA) in 802.11ax, the role of the Access Point (AP) in Wi-Fi networks changes significantly, thanks to the opportunity of implementing more complex scheduling logic to handle Downlink (DL) traffic flows and simultaneously act as coordinator of Multi User (MU) Uplink (UL) transmissions. In this context, it becomes necessary to develop reliable network analysis and simulation tools that allow for an in-depth investigation of the trade-offs involved in the usage of OFDMA, especially considering that the standard leaves much of the actual scheduling algorithmic details to vendor-specific implementation. In this work we present a series of results highlighting how several network settings have an impact on throughput and Head-of-Line Delay, in a network that employs multiple 802.11ax features such as OFDMA and the MU Enhanced Distributed Channel Access (EDCA) Parameter Set, while also containing legacy devices. The results are obtained via both the newly re-designed ns-3 wifi module and an original analytical framework, based on the well-established Bianchi 802.11 model
On spectrum sensing in cognitive radio CDMA networks with beamforming
No full textIn this paper, the performance of cognitive radio (CR) code division multiple access (CDMA) networks is analyzed in the presence of receive beamforming at the base stations (BSs). More precisely, we analyze, through simulations, the performance achievable by a CR user, with and without spectrum sensing, in a three-cell scenario. Uplink communications are considered. Three different schemes for spectrum sensing with beamforming are presented, together with a scheme without spectrum sensing. CR users belong to a cognitive radio network (CRN) which is coexisting with a primary radio network (PRN). Both the CRN and the PRN are CDMA based. The CRN is assumed to utilize beamforming for its CR users. Soft hand-off (HO) and power control are considered in both the CRN and the PRN. The impact of beamforming on the system performance is analyzed, considering various metrics. In particular, we evaluate the performance of the proposed systems in terms of outage probability, blocking probability, and average data rate of CR users. The results obtained clearly indicate that significant performance improvements can be obtained by CR users with the help of beamforming. The impact of several system parameters on the performance of the three considered spectrum sensing schemes with beamforming is analyzed. Our results, in terms of probability of outage, show that the relative improvement brought by the use of beamforming is higher in the absence of spectrum sensing (reduction of 80%) than in the presence of spectrum sensing (reduction of 42%)
Performance analysis of the WiNC2R platform:
No full textA Cognitive Radio (CR) is an intelligent transceiver device, able to support multiple technologies, dynamic re-configurability, ease of programming and collaboration with other CR devices to improve the communication efficiency. The two key requirements for an efficient CR implementation are flexibility in operation/programming and speed.
WiNC2R (Winlab Network Centric Cognitive Radio) achieves high speed of operation using its hardware platform and flexibility using its software-configurable architecture. The current WiNC2R architecture implements an 802.11a-like OFDM flow. We evaluate the WiNC2R hardware architecture to see the modularity in the architecture, separation of data and control flow and the performance in terms of latency and throughput. To test the system, the Xilinx Bus Functional Model environment, which is designed to test the IBM standard bus-architecture-based hardware systems, is used. We use a simple ALOHA protocol in the MAC layer to communicate between two WiNC2R nodes and evaluate the performance under the best-case scenario, where the performance is only hindered by the architecture itself rather than external conditions like channel state.
The results of our basic experiments showed that for a single OFDM 802.11a-like flow, the Unit Control Modules (UCM) were idle for almost 80% of the total processing time.
We then tested the WiNC2R system to study the effects of changing the frame size. It was seen that the latencies in the WiNC2R transmitter are frame-size dependent while those in the receiver mainly depend on the size of the data in the last chunk rather than the size of the whole frame. We suggest that chunk size should be 2 OFDM symbols, and chunking be moved to MAC layer for better performance. We give analytical estimates of resulting performance improvement. In the next experiment, we describe virtualization in the WiNC2R by adding more flows. We describe the steps to implement the additional flows and estimate maximum number of concurrent flows possible.
In the last analysis, we show the effect of operating clock frequency on the performance. We prove that at 250 MHz operating frequency and 2 OFDM symbols per chunk, the current WiNC2R implementation will be able to satisfy the SIFS criterion.M.S.Includes bibliographical references (p. 72-73)by Sumit Satarka
Censoring-based Cooperative Spectrum Sensing with Improved Energy Detectors and Multiple Antennas in Fading Channels
No full textIn the current work, the performance of cooperative spectrum sensing (CSS) with threshold-based censoring is investigated in the presence of noisy and faded environments. In particular, scenarios with Rayleigh, Hoyt, and Rician fading, affecting both the sensing (S) and reporting (R) channels, are considered. Each secondary user (SU) is equipped with multiple antennas and relies on an improved energy detector (IED). More precisely, the signals from the primary user (PU), received by multiple antennas of a SU, are fed to the IED, the IED outputs are combined using a selection combiner (SC), and the combined signal is used to make a local decision. At the fusion center (FC), censoring of SUs is done on the basis of the quality, evaluated by the FC, of the faded R-channels. The censored decisions received at the FC are fused, using majority logic or maximal ratio combining (MRC), to obtain a final decision on the status of the PU. The performance of CSS, in terms of average miss detection probability and error rate, is evaluated considering the impact of relevant network parameters. Optimized values of the censoring threshold, as well as of the required parameters of the IED, are determined under several network conditions. The performance of the proposed IED is compared with that of a conventional energy detector (CED)
Cooperative Spectrum Sensing with Censoring of Cognitive Radios in Fading Channel Under Majority Logic Fusion
No full textIn a cooperative spectrum sensing (CSS) scheme, the detection of the presence of activity of a primary user (PU) is improved by the fact that several cognitive radio (CR) users send, through reporting channels (R-channels), their sensed information on the activity of this PU to a common base station (BS). The benefits are particularly relevant in scenarios where the sensing channels (S-channels) towards the PU of interest of CR users are affected by severe fading or shadowing. However, in a CSS scheme with R channels affected by fading or shadowing as well, there may be erroneous reception, at the BS, of decisions from CR users: this can be counter-acted by using censoring of CR users. In this chapter, we discuss the performance of CSS with censoring of CR users based on their R-channels’ statuses. Two schemes of censoring are considered: (i) rank-based censoring, where a pre-defined number of CR users, associated with the best R-channels, are selected; and (ii) threshold-based censoring, where CR users, whose R-channel fading coefficients exceed a pre-determined threshold, are selected. The performance of both censoring schemes is evaluated considering two different R-channel fading conditions: (i) Rayleigh fading and (ii) Nakagami- m fading. In both cases, majority logic fusion is considered at the BS (also denoted re-interpreted as fusion center, FC). The impact of various network parameters—such as censoring threshold, number of CR users, average S-and R-channels’ SNRs, channel estimation (CE) quality, and fading severity—on the performance of the considered CSS schemes will be evaluated in terms of missed detection and total error probabilities
Throughput and delay analysis of cognitive M2M communications
Get PDFIn this paper, we analyze throughput and delay performance of clustered Machine Type Communication (MTC) devices which access an eNodeB utilizing a primary spectrum in underlay mode. We assume that the MTC devices form two clusters and there is an optimal preamble allocation between the two clusters to maximize the throughput. We further investigate the impact of the tolerable interference threshold on throughput, successful preamble decoding probability, and delay. Then, the impact of the preamble partition factor and the access barring factor on throughput and delay is analyzed. Finally, we evaluate the impact of the number of devices, retransmission requests, and preamble partitions on the delay
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