Simulation of A Communications System Using Matlab

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Polytechnique Montreal

The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

Simulation of A Communications System Using Matlab

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In this paper, we propose an adaptive medium access control (MAC) protocol for full-duplex (FD) cognitive radio networks in which FD secondary users (SUs) perform channel contention followed by concurrent spectrum sensing and transmission, and transmission only with maximum power in two different stages (called the FD sensing and transmission stages, respectively) in each contention and access cycle. The proposed FD cognitive MAC (FDC-MAC) protocol does not require synchronization among SUs, and it efciently utilizes the spectrum and mitigates the self-interference in the FD transceiver. We develop a mathematical model to analyze the throughput performance of the FDC-MAC protocol, where both half-duplex (HD) transmission and FD transmission modes are considered in the transmission stage. Then, we study the FDC-MAC conguration optimization through adaptively controlling the spectrum sensing duration and transmit power level in the FD sensing stage.We prove that there exists optimal sensing time and transmit power to achieve the maximum throughput, and we develop an algorithm to congure the proposed FDC-MAC protocol. Extensive numerical results are presented to illustrate the optimal FDC-MAC conguration and the impacts of protocol parameters and the self-interference cancellation quality on the throughput performance. Moreover, we demonstrate the signicant throughput gains of the FDC-MAC protocol with respect to the existing HD MAC and single-stage FD MAC protocols

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In this paper, we propose a semi-distributed cooperative spectrum sen sing (SDCSS) and channel access framework for multi-channel cognitive radio networks (CRNs). In particular, we c onsider a SDCSS scheme where secondary users (SUs) perform sensing and exchange sensing outcomes with ea ch other to locate spectrum holes. In addition, we devise the p -persistent CSMA-based cognitive MAC protocol integrating the SDCSS to enable efficient spectrum sharing among SUs. We then perform throughput analysis and develop an algorithm to determine the spectrum sensing and access parameters to maximize the throughput for a given allocation of channel sensing sets. Moreover, we consider the spectrum sensing set optimization problem for SUs to maxim ize the overall system throughput. We present both exhaustive search and low-complexity greedy algorithms to determine the sensing sets for SUs and analyze their complexity. We also show how our design and analysis can be extended to consider reporting errors. Finally, extensive numerical results are presented to demonstrate the sig nificant performance gain of our optimized design framework with respect to non-optimized designs as well as the imp acts of different protocol parameters on the throughput performance.

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In order to improve sensing performance when the noise variance is not known, this paper considers a so-called blind spectrum sensing technique that is based on eigenvalue models. In this paper, we employed the spiked population models in order to identify the miss detection probability. At first, we try to estimate the unknown noise variance based on the blind measurements at a secondary location. We then investigate the performance of detection, in terms of both theoretical and empirical aspects, after applying this estimated noise variance result. In addition, we study the effects of the number of SUs and the number of samples on the spectrum sensing performance.

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This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology. At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance. In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.

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In this paper, we propose an exact analytical technique to evaluate the average capacity of a dual-hop OFDM relay system with decode-and-forward protocol in an independent and identical distribution (i.i.d.) Rayleigh fading channel. Four schemes, (no) matching “and” or “or” (no) power allocation, will be considered. First, the probability density function (pdf) for the end-to-end power channel gain for each scheme is described. Then, based on these pdf functions, we will give the expressions of the average capacity. Monte Carlo simulation results will be shown to confirm the analytical results for both the pdf functions and average capacities.

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In this paper, we apply the maximal ratio combining (MRC) technique to achieve higher detection probability in cognitive radio networks over correlated Rayleigh fading channels. We present a simple approach to derive the probability of detection in closed-form expression. The numerical results reveal that the detection performance is a monotonically increasing function with respect to the number of antennas. Moreover, we provide sets of complementary receiver operating characteristic (ROC) curves to illustrate the effect of antenna correlation on the sensing performance of cognitive radio networks employing MRC schemes in some respective scenarios.

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In cognitive radio (CR) networks, unlicensed (cognitive) users can exploit the licensed frequency bands by using spectrum sensing techniques to identify spectrum holes. This paper proposes a distributed compressive spectrum sensing scheme, in which the modulated wide-band converter can apply compressed sensing (CS) directly to analog signals at the sub-Nyquist rate and the central fusion receives signals from multiple CRs and exploits the multiple-measurements-vectors (MMV) subspace pursuit (M-SP) algorithm to jointly reconstruct the spectral support of the wide-band signal. This support is then used to detect whether the licensed bands are occupy or not. Finally, extensive simulation results show the advantages of the proposed scheme. Besides, we also compare the performance of M-SP with M-orthogonal matching pursuit (M-OMP) algorithms.

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Cognitive radio allows unlicensed (cognitive) users to use licensed frequency bands by exploiting spectrum sensing techniques to detect whether or not the licensed (primary) users are present. In this paper, we present a compressed sensing applied to spectrum-occupancy detection in wide-band applications. The collected analog signals from each cognitive radio (CR) receiver at a fusion center are transformed to discrete-time signals by using analog-to-information converter (AIC) and then employed to calculate the autocorrelation. For signal reconstruction, we exploit a novel approach to solve the optimization problem consisting of minimizing both a quadratic (l2) error term and an l1-regularization term. In specific, we propose the Basic gradient projection (GP) and projected Barzilai-Borwein (PBB) algorithm to offer a better performance in terms of the mean squared error of the power spectrum density estimate and the detection probability of licensed signal occupancy.

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In this paper, we investigate the joint cooperative spectrum sensing and access design problem for multi-channel cognitive radio networks. A general heterogeneous setting is considered where the probabilities that different channels are available, SNRs of the signals received at secondary users (SUs) due to transmissions from primary users (PUs) for different users and channels can be different. We assume a cooperative sensing strategy with a general a-out-of-b aggregation rule and design a synchronized MAC protocol so that SUs can exploit available channels. We analyze the sensing performance and the throughput achieved by the joint sensing and access design. Based on this analysis, we develop algorithms to find optimal parameters for the sensing and access protocols and to determine channel assignment for SUs to maximize the system throughput. Finally, numerical results are presented to verify the effectiveness of our design and demonstrate the relative performance of our proposed algorithms and the optimal ones.

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In this paper, we consider the channel allocation problem for throughput maximization in cognitive radio networks with hardware-constrained secondary users. Specifically, we assume that secondary users exploit spectrum holes on a set of channels where each secondary user can use at most one available channel for communication. We develop two channel assignment algorithms that can efficiently utilize spectrum opportunities on these channels. In the first algorithm, secondary users are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm, that can improve the throughput performance compared to the non-overlapping channel assignment algorithm. In addition, we design a distributed MAC protocol for access contention resolution and integrate the derived MAC protocol overhead into the second channel assignment algorithm. Finally, numerical results are presented to validate the theoretical results and illustrate the performance gain due to the overlapping channel assignment algorithm.

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Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

"Impact of front-end architecture on development cost", Viktor Turskyi

"Impact of front-end architecture on development cost", Viktor Turskyi

"Impact of front-end architecture on development cost", Viktor Turskyi

Designing Great Products: The Power of Design and Leadership by Chief Designe...

Designing Great Products: The Power of Design and Leadership by Chief Designe...

Designing Great Products: The Power of Design and Leadership by Chief Designe...

Optimizing NoSQL Performance Through Observability

Optimizing NoSQL Performance Through Observability

Optimizing NoSQL Performance Through Observability

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...

Search and Society: Reimagining Information Access for Radical Futures

Search and Society: Reimagining Information Access for Radical Futures

Search and Society: Reimagining Information Access for Radical Futures

Knowledge engineering: from people to machines and back

Knowledge engineering: from people to machines and back

Knowledge engineering: from people to machines and back

Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl

Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl

Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl

Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...

Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...

Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

Demystifying gRPC in .Net by John Staveley

Demystifying gRPC in .Net by John Staveley

Demystifying gRPC in .Net by John Staveley

Integrating Telephony Systems with Salesforce: Insights and Considerations, B...

Integrating Telephony Systems with Salesforce: Insights and Considerations, B...

Integrating Telephony Systems with Salesforce: Insights and Considerations, B...

SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...

SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...

SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...

GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...

GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...

GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...

AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...

AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...

AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

IESVE for Early Stage Design and Planning

IESVE for Early Stage Design and Planning

IESVE for Early Stage Design and Planning

Bits & Pixels using AI for Good.........

Bits & Pixels using AI for Good.........

Bits & Pixels using AI for Good.........

Assuring Contact Center Experiences for Your Customers With ThousandEyes

Assuring Contact Center Experiences for Your Customers With ThousandEyes

Assuring Contact Center Experiences for Your Customers With ThousandEyes