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Hamid, Mohamed
Publications (10 of 19) Show all publications
Hamid, M., Björsell, N. & Slimane, B. (2016). Energy and Eigenvalue-Based Combined Fully-Blind Self-Adapted Spectrum Sensing Algorithm. IEEE Transactions on Vehicular Technology, 65(2), 630-642
Open this publication in new window or tab >>Energy and Eigenvalue-Based Combined Fully-Blind Self-Adapted Spectrum Sensing Algorithm
2016 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 65, no 2, p. 630-642Article in journal (Refereed) Published
Abstract [en]

In this paper, a comparison between energy and maximum-minimum eigenvalue detectors is performed. The comparison has been made concerning the sensing complexity and the sensing accuracy in terms of the receiver operating characteristics curves. The impact of the signal bandwidth compared to the observation bandwidth is studied for each detector. For the energy detector, the probability of detection increases monotonically with the increase of the signal bandwidth. For the maximum-minimum eigenvalue detector, an optimal value of the ratio between the signal bandwidth and the observation bandwidth is found to be 0.5 when reasonable values of the system dimensionality are used. Based on the comparison findings, a combined two-stage detector is proposed. The combined detector performance is evaluated based on simulations and measurements. The combined detector achieves better sensing accuracy than the two individual detectors with a complexity lies in between the two individual complexities. The combined detector is fully-blind and self-adapted as the maximum-minimum eigenvalue detector estimates the noise and feeds it back to the energy detector. The performance of the noise estimation process is evaluated in terms of the normalized mean square error.

Keywords
Blind sensing, Energy detector, Maximum-minimum eigenvalue detector, Multi-stage sensing, Noise estimation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-18957 (URN)10.1109/TVT.2015.2401132 (DOI)000370754000012 ()2-s2.0-84962176492 (Scopus ID)
Available from: 2015-02-10 Created: 2015-02-10 Last updated: 2018-03-13Bibliographically approved
Hamid, M., Slimane, B., Van Moer, W. & Björsell, N. (2016). Spectrum Sensing Challenges: Blind Sensing and Sensing Optimization. IEEE Instrumentation & Measurement Magazine, 19(2), 44-52
Open this publication in new window or tab >>Spectrum Sensing Challenges: Blind Sensing and Sensing Optimization
2016 (English)In: IEEE Instrumentation & Measurement Magazine, ISSN 1094-6969, E-ISSN 1941-0123, Vol. 19, no 2, p. 44-52Article in journal (Refereed) Published
Abstract [en]

By any measure, wireless communications is one of the most evolving fields in engineering. This, in return, has imposed many challenges, especially in handling the hunger for higher data rates in the next generation wireless networks. Among these challenges is how to provide the needed resources in terms of the electromagnetic radio spectrum for these networks. In this regard, cognitive radio (CR) based on dynamic spectrum access (DSA) has been attracting huge attention as a promising solution for more efficient utilization of the available radio spectrum. DSA is based on finding and opportunistically accessing the free-of-use portions of spectrum. To facilitate DSA, spectrum sensing can be used. However, spectrum sensing faces many challenges in different aspects. Such aspects include blind sensing and sensing optimization, which are both to a great extent measurement challenges. We discuss different contributions in addressing these two challenges in this article.

Keywords
cognitive radio, next generation networks, radio communication, radio systems, wireless networks, next generation wireless network, radio spectra
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-21563 (URN)10.1109/MIM.2016.7462794 (DOI)000375571400012 ()2-s2.0-84969534000 (Scopus ID)
Available from: 2016-06-10 Created: 2016-06-10 Last updated: 2019-09-05Bibliographically approved
Hamid, M. & Björsell, N. (2015). Frequency Hopping for Fair Radio Resources Allocation in TVWS. In: Carlos Becker Westphall, Iwona Pozniak-Koszalka, Eugen Borcoci & Dragana Krstic (Ed.), ICWMC 2015: The Eleventh International Conference onWireless and Mobile Communications. Paper presented at The Eleventh International Conference on Wireless and Mobile Communications (ICWMC 2015), October 11-16, 2015, St. Julians, Malta (pp. 71-76).
Open this publication in new window or tab >>Frequency Hopping for Fair Radio Resources Allocation in TVWS
2015 (English)In: ICWMC 2015: The Eleventh International Conference onWireless and Mobile Communications / [ed] Carlos Becker Westphall, Iwona Pozniak-Koszalka, Eugen Borcoci & Dragana Krstic, 2015, p. 71-76Conference paper, Published paper (Refereed)
Abstract [en]

Using frequency hopping for fair resources allocation in TV white spaces is proposed and evaluated in this paper. The degree of fairness is judged by the achieved throughput by different secondary users. The throughput of the secondary users is determined by their permissible transmission power and the interference from the TV and other secondary users. The permissible transmission power for secondary users in TV white spaces in different channels is investigated. The main concern of calculating the permissible secondary user transmission power is protecting the primary TV receivers from harmful interference. With the aid of SPLAT (RF Signal Propagation, Loss, And Terrain analysis tool), the received TV signal power in a study case of the surroundings of the city of Gävle is fetched. The interference from the TV transmission into the free channels is measured in six different locations. The simulated system is a deployed Wi-Fi access points in a building representing an office environment in an urban area. Moreover, the size of the hopping set and the number of APs influences are investigated.

Keywords
TV white spaces, Wi-Fi Access Points, Secondary Spectrum Access, Frequency Hopping, Throughput
National Category
Telecommunications
Identifiers
urn:nbn:se:hig:diva-21462 (URN)978-1-61208-433-6 (ISBN)
Conference
The Eleventh International Conference on Wireless and Mobile Communications (ICWMC 2015), October 11-16, 2015, St. Julians, Malta
Available from: 2016-05-03 Created: 2016-05-03 Last updated: 2018-03-13Bibliographically approved
Hamid, M., Björsell, N. & Ben Slimane, S. (2015). Signal Bandwidth Impact on Maximum-Minimum Eigenvalue Detection. IEEE Communications Letters, 19(3), 395-398, Article ID 7001062.
Open this publication in new window or tab >>Signal Bandwidth Impact on Maximum-Minimum Eigenvalue Detection
2015 (English)In: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 19, no 3, p. 395-398, article id 7001062Article in journal (Refereed) Published
Abstract [en]

The impact of the signal bandwidth and observation bandwidth on the detection performance of the maximumminimum eigenvalue detector is studied in this letter. The considered signals are the Gaussian signals. The optimum ratio between the signal and the observation bandwidth is analytically proven to be 0.5 when reasonable values of the system dimensionality are used. The analytical proof is verified by simulations.

Keywords
Bandwidth; Covariance matrices; Eigenvalues and eigenfunctions; Gaussian noise;Sensors;Signal to noise ratio; Detection bandwidth; Marchenko Pastur densit; Maximum-minimum eigenvalue detection; Occupation bandwidth
National Category
Signal Processing
Identifiers
urn:nbn:se:hig:diva-18675 (URN)10.1109/LCOMM.2014.2387287 (DOI)000351407800022 ()2-s2.0-84924911982 (Scopus ID)
Available from: 2015-01-07 Created: 2015-01-07 Last updated: 2018-03-13Bibliographically approved
Hamid, M., Björsell, N. & Slimane, B. S. (2014). Sample covariance matrix eigenvalues based blind SNR estimation. In: 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings: . Paper presented at I2MTC 2014, Montevideo, Uruguay, May 12-15, 2014 (pp. 718-722).
Open this publication in new window or tab >>Sample covariance matrix eigenvalues based blind SNR estimation
2014 (English)In: 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014, p. 718-722Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a newly developed SNR estimation algorithm is presented. The new algorithm is based on the eigenvalues of the samples covariance matrix of the recieved signal. The presented algorithm is blind in the sense that both the noise and the signal power are unknown and estimated from the received samples. The Minimum Descriptive Length (MDL) criterion is used to split the signal and noise corresponding eigenvalues. The experimental results are judged using the Normalized Mean Square Error (NMSE) between the estimated and the actual SNRs. The results show that depending on the value of received vectors size, N, and the number of received vectors, L, the NMSE is changed and down to −55 dB NMSE can be achieved for the highest used values of N and L.

Series
IEEE Instrumentation and Measurement Technology Conference, ISSN 1091-5281
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-16231 (URN)10.1109/I2MTC.2014.6860836 (DOI)000346477200138 ()2-s2.0-84905695374 (Scopus ID)978-146736385-3 (ISBN)
Conference
I2MTC 2014, Montevideo, Uruguay, May 12-15, 2014
Available from: 2014-01-30 Created: 2014-01-30 Last updated: 2018-03-13Bibliographically approved
Hamid, M., Björsell, N., Van Moer, W., Barbé, K. & Slimane, B. (2013). Blind Spectrum Sensing for Cognitive Radios Using Discriminant Analysis: A Novel Approach. IEEE Transactions on Instrumentation and Measurement, 62(11), 2912-2921
Open this publication in new window or tab >>Blind Spectrum Sensing for Cognitive Radios Using Discriminant Analysis: A Novel Approach
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2013 (English)In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 62, no 11, p. 2912-2921Article in journal (Refereed) Published
Abstract [en]

In this paper, we present a new spectrum sensing technique for cognitive radios based on discriminant analysis called spectrum discriminator. The presented technique uses the knowledge of the noise uncertainty and a probabilistic validation to overcome the limitations of the discriminant analysis. A comparative study between the proposed technique and the maximum-minimum eigenvalue detection has been performed based on two performance metrics: the probability of false alarm and the probability of detection. The spectrum discriminator has been further developed to a peel-off technique where all primary users can be detected. The performance of the spectrum discriminator and the peel-off technique has been tested on simulations and experimentally verified. The comparative study is based on simulations as well as measurements.

Keywords
Blind detection; cognitive radio; discriminant analysis; maximum-minimum eigenvalues detection; spectrum discriminator; spectrum sensing
National Category
Communication Systems Telecommunications
Identifiers
urn:nbn:se:hig:diva-14912 (URN)10.1109/TIM.2013.2267456 (DOI)000325820200004 ()2-s2.0-84885958005 (Scopus ID)
Available from: 2013-07-18 Created: 2013-07-18 Last updated: 2018-03-13Bibliographically approved
Hamid, M., Björsell, N. & Mohammed, A. (2013). Iterative Optimization of Energy Detector Sensing Time and Periodic Sensing Interval in Cognitive Radio Networks (1ed.). In: Anwer Al-Dulaimi, John Cosmas, Abbas Mohammed (Ed.), Self-Organization and Green Applications in Cognitive Radio Networks: (pp. 53-69). IGI Global
Open this publication in new window or tab >>Iterative Optimization of Energy Detector Sensing Time and Periodic Sensing Interval in Cognitive Radio Networks
2013 (English)In: Self-Organization and Green Applications in Cognitive Radio Networks / [ed] Anwer Al-Dulaimi, John Cosmas, Abbas Mohammed, IGI Global, 2013, 1, p. 53-69Chapter in book (Refereed)
Abstract [en]

In this chapter the authors propose a new approach for optimizing the sensing time and periodic sensing interval for energy detectors in cognitive radio networks. The optimization of the sensing time depends on maximizing the summation of the probability of right detection and transmission efficiency, while the optimization of periodic sensing interval is subject to maximizing the summation of transmission efficiency and captured opportunities. Since the optimum sensing time and periodic sensing interval are dependent on each other, an iterative approach to optimize them simultaneously is proposed and a convergence criterion is devised. In addition, the probability of detection, probability of false alarm, probability of right detection, transmission efficiency, and captured opportunities are taken as performance metrics for the detector and evaluated for various values of channel utilization factors and signal-to-noise ratios.

Place, publisher, year, edition, pages
IGI Global, 2013 Edition: 1
National Category
Communication Systems
Identifiers
urn:nbn:se:hig:diva-13979 (URN)10.4018/978-1-4666-2812-0.ch003 (DOI)2-s2.0-84898167667 (Scopus ID)9781466628120 (ISBN)
Available from: 2013-03-21 Created: 2013-03-21 Last updated: 2018-03-13Bibliographically approved
Hamid, M. & Mohammed, A. (2013). MAC Layer Spectrum Sensing in Cognitive Radio Networks (1ed.). In: Anwer Al-Dulaimi, John Cosmas, Abbas Mohammed (Ed.), Self-Organization and Green Applications in Cognitive Radio Networks: (pp. 210-230). IGI Global
Open this publication in new window or tab >>MAC Layer Spectrum Sensing in Cognitive Radio Networks
2013 (English)In: Self-Organization and Green Applications in Cognitive Radio Networks / [ed] Anwer Al-Dulaimi, John Cosmas, Abbas Mohammed, IGI Global, 2013, 1, p. 210-230Chapter in book (Refereed)
Abstract [en]

Efficient use of the available licensed radio spectrum is becoming increasingly difficult as the demand and usage of the radio spectrum increases. This usage of the spectrum is not uniform within the licensed band but concentrated in certain frequencies of the spectrum while other parts of the spectrum are inefficiently utilized. In cognitive radio environments, the primary users are allocated licensed frequency bands while secondary cognitive users can dynamically allocate the empty frequencies within the licensed frequency band, according to their requested quality of service specifications. In this chapter, the authors investigate and assess the performance of MAC layer sensing schemes in cognitive radio networks. Two performance metrics are used to assess the performance of the sensing schemes: the available spectrum utilization and the idle channel search delay for reactive and proactive sensing schemes. In proactive sensing, the adapted and non-adapted sensing period schemes are also assessed. Simulation results show that proactive sensing with adapted periods provides superior performance at the expense of higher computational cost performed by network nodes.

Place, publisher, year, edition, pages
IGI Global, 2013 Edition: 1
National Category
Communication Systems
Identifiers
urn:nbn:se:hig:diva-13980 (URN)10.4018/978-1-4666-2812-0.ch010 (DOI)2-s2.0-84898261769 (Scopus ID)978-146662812-0 (ISBN)9781466628137 (ISBN)
Available from: 2013-03-21 Created: 2013-03-21 Last updated: 2018-03-13Bibliographically approved
Hamid, M., Ferrer Coll, J., Björsell, N., Chilo, J. & Van Moer, W. (2013). Multi-Interference Detection Algorithm using Discriminant Analysis in Industrial Environments. In: 39th Annual Conference of the IEEE Industrial Electronics Society (IECON 2013): . Paper presented at 39th Annual Conference of the IEEE Industrial Electronics Society (IECON 2013), November 10-13 2013, Vienna, Austria (pp. 5600-5604). New York: IEEE conference proceedings
Open this publication in new window or tab >>Multi-Interference Detection Algorithm using Discriminant Analysis in Industrial Environments
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2013 (English)In: 39th Annual Conference of the IEEE Industrial Electronics Society (IECON 2013), New York: IEEE conference proceedings, 2013, p. 5600-5604Conference paper, Published paper (Refereed)
Abstract [en]

In this paper a technique to detect multiple impulsive interference in an industrial environment is proposed and evaluated. The technique is based on discriminant analysis which iteratively peels-off the impulsive interferences. The probability of detection of the technique is tested with and without the iterative peeling-off part. The simulations show that the SIR can be improved by applying the detection technique and then blank or clip the impulsive interference components. The improvement in the SIR depends on the impulsive interference parameters and it can reach up to 17 dB.

Place, publisher, year, edition, pages
New York: IEEE conference proceedings, 2013
Series
IEEE Industrial Electronics Society, ISSN 1553-572X
Keywords
Wireless communications, impulsive interference, detection techniques
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-14516 (URN)10.1109/IECON.2013.6700051 (DOI)000331149505075 ()2-s2.0-84893531226 (Scopus ID)978-1-4799-0224-8 (ISBN)
Conference
39th Annual Conference of the IEEE Industrial Electronics Society (IECON 2013), November 10-13 2013, Vienna, Austria
Available from: 2013-06-15 Created: 2013-06-15 Last updated: 2018-03-13Bibliographically approved
Hamid, M. (2013). On Finding Spectrum Opportunities in Cognitive Radios: Spectrum Sensing and Geo-locations Database. (Licentiate dissertation). Stockholm: KTH Royal Institute of Technology
Open this publication in new window or tab >>On Finding Spectrum Opportunities in Cognitive Radios: Spectrum Sensing and Geo-locations Database
2013 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The spectacular growth in wireless services imposes scarcity in term of the available radio spectrum. A solution to overcome this scarcity is to adopt what so called cognitive radio based on dynamic spectrum access. With dynamic spectrum access, secondary (unlicensed) users can access spectrum owned by primary (licensed) users when it is temporally and/or geographically unused. This unused spectrum is termed as spectrum opportunity. Finding these spectrum opportunities related aspects are studied in this thesis where two approaches of finding spectrum opportunities, namely spectrum sensing and geo-locations databases are considered.

In spectrum sensing arena, two topics are covered, blind spectrum sensing and sensing time and periodic sensing interval optimization. For blind spectrum sensing, a spectrum scanner based on maximum minimum eigenvalues detector and frequency domain rectangular filtering is developed. The measurements show that the proposed scanner outperforms the energy detector scanner in terms of the probability of detection. Continuing in blind spectrum sensing, a novel blind spectrum sensing technique based on discriminant analysis called spectrum discriminator has been developed in this thesis. Spectrum discriminator has been further developed to peel off multiple primary users with different transmission power from a wideband sensed spectrum. The spectrum discriminator performance is measured and compared with the maximum minimum eigenvalues detector in terms of the probability of false alarm, the probability of detection and the sensing time.

For sensing time and periodic sensing interval optimization, a new approach that aims at maximizing the probability of right detection, the transmission efficiency and the captured opportunities is proposed and simulated. The proposed approach optimizes the sensing time and the periodic sensing interval iteratively. Additionally, the periodic sensing intervals for multiple channels are optimized to achieve as low sensing overhead and unexplored opportunities as possible for a multi channels system.

The thesis considers radar bands and TV broadcasting bands to adopt geo-locations databases for spectrum opportunities. For radar bands, the possibility of spectrum sharing with secondary users in L, S and C bands is investigated. The simulation results show that band sharing is possible with more spectrum opportunities offered by C band than S and L band which comes as the least one. For the TV broadcasting bands, the thesis treats the power assignment for secondary users operate in Gävle area, Sweden. Furthermore, the interference that the TV transmitter would cause to the secondary users is measured in different locations in the same area.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. p. 78
National Category
Communication Systems
Identifiers
urn:nbn:se:hig:diva-13644 (URN)
Presentation
2013-02-07, 99:132, University of Gävle, Kungsbäacksvägen 47, Gävle, 15:51 (English)
Opponent
Supervisors
Available from: 2013-09-15 Created: 2013-01-11 Last updated: 2018-03-13Bibliographically approved
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