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Masoumeh Nasiri-Kenari

Publications and source records attributed to Masoumeh Nasiri-Kenari.

45 records · Page 3Linked to original sources
arXiv2014

Compute-and-Forward Two-Way Relaying

In this paper, a new two-way relaying scheme based on compute-and-forward (CMF) framework and relay selection strategies is proposed, which provides a higher throughput than the conventional two-way relaying schemes. Two cases of relays with or without feedback transmission capability are considered. An upper bound on the computation rate of each relay is derived, and based on that, a lower bound on the outage probability of the system is presented assuming block Rayleigh fading channels. Numerical results show that while the average sum rate of the system without feedback, named as Max Compute-and-Forward (M-CMF), reaches the derived upper bound only in low SNRs, that of the system with feedback, named as Aligned Compute-and-Forward (A-CMF) reaches the bound in all SNRs. However, both schemes approach the derived lower bound on the outage probability in all SNRs.

cs.IT↗
arXiv2013

Convolutional Network-Coded Cooperation in Multi-Source Networks with a Multi-Antenna Relay

We propose a novel cooperative transmission scheme called "Convolutional Network-Coded Cooperation" (CNCC) for a network including N sources, one M-antenna relay, and one common destination. The source-relay (S-R) channels are assumed to be Nakagami-m fading, while the source-destination (S-D) and the relay-destination (R-D) channels are considered Rayleigh fading. The CNCC scheme exploits the generator matrix of a good (N+M', N, v) systematic convolutional code, with the free distance of d_free designed over GF(2), as the network coding matrix which is run by the network's nodes, such that the systematic symbols are directly transmitted from the sources, and the parity symbols are sent by the best antenna of the relay. An upper bound on the BER of the sources, and consequently, the achieved diversity orders are obtained. The numerical results indicate that the CNCC scheme outperforms the other cooperative schemes considered, in terms of the diversity order and the network throughput. The simulation results confirm the accuracy of the theoretical analysis.

cs.NI↗
arXiv2013

Simplified Compute-and-Forward and Its Performance Analysis

The compute-and-forward (CMF) method has shown a great promise as an innovative approach to exploit interference toward achieving higher network throughput. The CMF was primarily introduced by means of information theory tools. While there have been some recent works discussing different aspects of efficient and practical implementation of CMF, there are still some issues that are not covered. In this paper, we first introduce a method to decrease the implementation complexity of the CMF method. We then evaluate the exact outage probability of our proposed simplified CMF scheme, and hereby provide an upper bound on the outage probability of the optimum CMF in all SNR values, and a close approximation of its outage probability in low SNR regimes. We also evaluate the effect of the channel estimation error (CEE) on the performance of both optimum and our proposed simplified CMF by simulations. Our simulation results indicate that the proposed method is more robust against CEE than the optimum CMF method for the examples considered.

cs.IT↗
arXiv2013

A Cooperative MARC Scheme Using Analogue Network Coding to Achieve Second-Order Diversity

A multiple access relay channel (MARC) is considered in which an analogue-like network coding is implemented in the relay node. This analogue coding is a simple addition of the received signals at the relay node. Using "nulling detection" structure employed in V-BLAST receiver, we propose a detection scheme in the destination which is able to provide a diversity order of two for all users. We analytically evaluate the performance of our proposed scheme for the MARC with two users where tight upper bounds for both uncoded and Convolutionally coded transmission blocks are provided. We verify our analytical evaluations by simulations and compare the results with those of noncooperative transmission and Alamouti's scheme for the same power and rate transmission. Our results indicate that while our proposed scheme shows a comparable performance compared to the Alamouti's scheme, it substantially outperforms the non-cooperate transmission.

cs.IT↗
arXiv2012

Performance Analysis of Sequential Method for Handover in Cognitive Radio Systems

Powerful spectrum handover schemes enable cognitive radios (CRs) to use transmission opportunities in primary users' channels appropriately. In this paper, we consider the cognitive access of primary channels by a secondary user. We evaluate the average detection time and the maximum achievable average throughput of the secondary user when the sequential method for hand-over (SMHO) is used. We assume that a prior knowledge of the primary users' presence and absence probabilities are available. When investigating the maximum achievable throughput of the secondary user, we end into an optimization problem, in which the optimum value of sensing time must be selected. In our optimization problem, we take into account the spectrum hand over due to false detection of the primary user. We also propose a weighted based hand-over (WBHO) scheme in which the impacts of channels conditions and primary users' presence probability are considered. This Spectrum handover scheme provides higher average throughput for the SU than the SMHO method. The tradeoff between the maximum achievable throughput and consumed energy is discussed, and finally an energy efficient optimization formulation for finding a proper sensing time is provided.

cs.PF↗
arXiv2012

Sensing Matrix Setting Schemes for Cognitive Networks and Their Performance Analysis

Powerful spectrum decision schemes enable cognitive radios (CRs) to find transmission opportunities in spectral resources allocated exclusively to the primary users. One of the key effecting factor on the CR network throughput is the spectrum sensing sequence used by each secondary user. In this paper, secondary users' throughput maximization through finding an appropriate sensing matrix (SM) is investigated. To this end, first the average throughput of the CR network is evaluated for a given SM. Then, an optimization problem based on the maximization of the network throughput is formulated in order to find the optimal SM. As the optimum solution is very complicated, to avoid its major challenges, three novel sub optimum solutions for finding an appropriate SM are proposed for various cases including perfect and non-perfect sensing. Despite of having less computational complexities as well as lower consumed energies, the proposed solutions perform quite well compared to the optimum solution (the optimum SM). The structure and performance of the proposed SM setting schemes are discussed in detail and a set of illustrative simulation results is presented to validate their efficiencies.

cs.PF↗
arXiv2011

Analytical and Learning-Based Spectrum Sensing Time Optimization in Cognitive Radio Systems

Powerful spectrum sensing schemes enable cognitive radios (CRs) to find transmission opportunities in spectral resources allocated exclusively to the primary users. In this paper, maximizing the average throughput of a secondary user by optimizing its spectrum sensing time is formulated assuming that a prior knowledge of the presence and absence probabilities of the primary users is available. The energy consumed for finding a transmission opportunity is evaluated and a discussion on the impact of the number of the primary users on the secondary user throughput and consumed energy is presented. In order to avoid the challenges associated with the analytical method, as a second solution, a systematic neural network-based sensing time optimization approach is also proposed in this paper. The proposed adaptive scheme is able to find the optimum value of the channel sensing time without any prior knowledge or assumption about the wireless environment. The structure, performance, and cooperation of the artificial neural networks used in the proposed method are disclosed in detail and a set of illustrative simulation results is presented to validate the analytical results as well as the performance of the proposed learning-based optimization scheme.

cs.NI↗