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      • Open Access Article

        1 - The Impact of IQ Imbalance on the BER of Adaptive Modulation in the MIMO System
        Hooman Tahayori abbas mohammadi abdolali abdipour
        Abstract The effect of IQ imbalance on adaptive MQAM modulation in MIMO systems with direct conversion receivers is investigated in this paper. A continues power, discrete rate adaptive modulation scheme in using MIMO system with perfect channel information in both tran More
        Abstract The effect of IQ imbalance on adaptive MQAM modulation in MIMO systems with direct conversion receivers is investigated in this paper. A continues power, discrete rate adaptive modulation scheme in using MIMO system with perfect channel information in both transmitter and receiver is considered. The selected adaptation mechanism changes the transmit power and transmit constellation size under an average transmit power and instantaneous bit error rate (BER) constraints to obtain the maximum average spectral efficiency. First, a closed from expression for the BER of MQAM modulation under the effect of IQ imbalance is introduce. Then, the impact of IQ imbalance on the BER of adaptive modulation in MIMO system is studied. This effect is also investigated for the different configuration of trancmit-recive antenna. The analytic results are compared with the Mont Carlo simulation results to verify the analytic expression. Manuscript profile
      • Open Access Article

        2 - A new reinforcement learning based multi-agent method for traffic shaping and buffer allocation in routers
        Hooman Tahayori
        Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 More
        Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal" mso-tstyle-rowband-size:0 mso-tstyle-colband-size:0 mso-style-noshow:yes mso-style-priority:99 mso-style-qformat:yes mso-style-parent:"" mso-padding-alt:0cm 5.4pt 0cm 5.4pt mso-para-margin:0cm mso-para-margin-bottom:.0001pt mso-pagination:widow-orphan font-size:11.0pt font-family:"Calibri","sans-serif" mso-ascii-font-family:Calibri mso-ascii-theme-font:minor-latin mso-fareast-font-family:"Times New Roman" mso-fareast-theme-font:minor-fareast mso-hansi-font-family:Calibri mso-hansi-theme-font:minor-latin mso-bidi-font-family:Arial mso-bidi-theme-font:minor-bidi} Abstract In this paper, realizing the distributed structure of computer networks, the random behaviors in such networks, and the time limitations for control algorithms, the concepts of reinforcement learning and multi-agent systems are invoked for traffic shaping and buffer allocation between various ports of a router. In fact, a new traffic shaper based on token bucket has been developed. In this traffic shaper, instead of a static token production rate, a dynamic and intelligent rate based on the network condition is specified. This results in a reasonable utilization of bandwidth while preventing traffic overload in other part of the network. Besides, based on the stated techniques a new method for dynamic buffer allocation in the ports of a router is developed. This leads to a reduction in the total number of packet dropping in the whole network. Simulation results show the effectiveness of the proposed techniques. Manuscript profile
      • Open Access Article

        3 - Cross-layer Design for Congestion Control, Routing and Scheduling in Ad-hoc Wireless Networks with considering the Electrical Power of nodes
        Hooman Tahayori
        Abstract Ad hoc Wireless Networks, are networks formed by a collection of nodes through radio. In wireless networking environment, formidable challenges are presented. One important challenge is connection maintenance mechanism for power consumption. In this paper, a mu More
        Abstract Ad hoc Wireless Networks, are networks formed by a collection of nodes through radio. In wireless networking environment, formidable challenges are presented. One important challenge is connection maintenance mechanism for power consumption. In this paper, a multi-objective optimal design is considered for ad-hoc networks which address the electrical power of nodes effects on cross-layer congestion control, routing and scheduling. We first formulate the rate and scheduling constraints. In this way, the multi-commodity flow variables are used. Then, resource allocation in networks with fixed wireless channel and single-rate devices is formulated. Since the electrical power of nodes effects are included in the design problem, we formulate resource allocation as utility and cost function, together in a maximization problem with those constraints. By dual decomposition, the resource allocation problem vertically decomposes into three sub-problems: congestion control, routing and scheduling. These three sub-problems interact through congestion and link price. Simulation results are included to verify the effectiveness of the proposed approach. Manuscript profile
      • Open Access Article

        4 - Proposing an Information Retrieval Model Using Interval Numbers
        Hooman Tahayori farzad ghahremani
        Recent expansions of web demands for more capable information retrieval systems that more accurately address the users' information needs. Weighting the words and terms in documents plays an important role in any information retrieval system. Various methods for weighti More
        Recent expansions of web demands for more capable information retrieval systems that more accurately address the users' information needs. Weighting the words and terms in documents plays an important role in any information retrieval system. Various methods for weighting the words are proposed, however, it is not straightforward to assert which one is more effective than the others. In this paper, we have proposed a method that calculates the weights of the terms in documents and queries as interval numbers. The interval numbers are derived by aggregating the crisp weights that are calculated by exploiting the existing weighting methods. The proposed method, calculates an interval number as the overall relevancy of each document with the given query. We have discussed three approaches for ranking the interval relevancy numbers. In the experiments we have conducted on Cranfield and Medline datasets, we have studied the effects of weight normalization, use of variations of term and document frequency and have shown that appropriate selection of basic term weighting methods in conjunction with their aggregation into an interval number would considerably improve the information retrieval performance. Through appropriate selection of basic weighting methods we have reached the MAP of 0.43323 and 0.54580 on the datasets, respectively. Obtained results show that he proposed method, outperforms the use of any single basic weighting method and other existing complicated weighting methods. Manuscript profile