Ali Farzamnia

Multicasting Multiple Description Coding Using p-cycle Network Coding

This paper deliberates for a multimedia transmission scheme combining multiple description coding (MDC) and network coding (NC). Our goal is to take advantage from the property of MDC to provide quantized and compressed independent and identically distributed (iid) descriptions and also from the benefit of network coding, which uses network resources efficiently to recover lost data in the network. Recently, p-cycle NC has been introduced to recover and protect any lost or distorted descriptions at the receiver part exactly without need of retransmission. So far, MDC have not been explored using this type of NC. Compressed and coded descriptions are transmitted through the network where p-cycle NC is applied. P-cycle based algorithm is proposed for single and multiple descriptions lost. Results show that in the fixed bit rate, the PSNR (Peak Signal to Noise Ratio) of our reconstructed image and also subjective evaluation is improved significantly compared to previous work which is averaging method joint with MDC in order to conceal lost descriptions.

Efficient In-Band Spectrum Sensing Using Swarm Intelligence for Cognitive Radio Network

Spectrum sensing mechanisms enable cognitive radio networks to detect primary users (Upsi) and utilize spectrum holes for secondary user (SU) transmission. However, precise PU detection leads to longer sensing time and lower achievable throughput. In this paper, we propose a particle swarm optimization (PSO)-based scheme for an in-band local spectrum sensing to address the tradeoff between sensing time and throughput. Using methodological analysis, a fast convergence PSO (FC-PSO) scheme is derived by implementing a distribution-based stopping criterion subject to detection performance, optimization time, and SU gain. At the target probability of detection of at least 90%, the results show significant improvements of ~45% for sensing time, 70% for the probability of false alarm, and 12% for achievable throughput compared with nonoptimal sensing scheme at signal-to-noise ratio of 0 dB. FC-PSO also outperforms other optimization schemes in terms of convergence speed. The proposed scheme is proved to be an energy-efficient solution for practical implementation as it outperforms the other algorithms in terms of lower computational complexity as well as providing the best tradeoff values in meeting the objective function of sufficient opportunistic access for an SU under optimized sensing time for maximized throughput, while providing high protection to the PU.

Interference aware channel assignment (IACA) for cognitive wireless mesh networks

In this paper, we present the end-to-end interference aware concept of Cognitive wireless mesh network (CWMN). CWMN is the leading upcoming technology with the advantage of cognitive radio (CR). We demonstrate that the end-to-end interference model has the ability to perform better from SINR base model. To enhance the utilization of the unused spectrum the channel selection strategy should have some awareness mechanism to avoid interference. In this paper, novel interference aware channel assignment (IACA) algorithm is proposed. The end-to-end delay, packet delivery ratio and the throughput is used to estimate the performance of the proposed algorithm. The numerical results demonstrate that the proposed algorithm is closer to the optimum resource utilization.

Compressed Wavelet Packet-Based Spectrum Sensing With Adaptive Thresholding for Cognitive Radio

Cognitive radio is a system to utilize spectrum holes efficiently as a solution of spectrum scarcity. The availability of channels for secondary users is determined in the spectrum sensing phase by energy detection. Energy levels of sampled primary users (PUs) signal can be measured by wavelet transform with more accuracy compared with Fourier-based methods. Wavelet packet-based spectrum sensing measures the energy level at each subcarrier and sets the decision threshold. However, at the first step of energy detection for wideband spectrum sensing, high-rate analog-to-digital converter (ADC) sampling requires a large dynamic range and high-speed signal processors. In this paper, compressed sampling for PUs signal acquisition is proposed to reduce the rate of sampling and solve the implementation complexity of ADC. The simulation results verify that this mechanism is promising to estimate the power spectrum density (PSD) of PUs signals. The graphs prove low side-lobes of the detected PSD and acceptable probability of detection and false alarm due to the target values and certain compression ratio.

Wavelet Packet-Based Transceiver for Cognitive UWBÉmetteur-récepteurà base de paquet d'ondelette pour les applications cognitives UWB

Wideband spectrum in cognitive ultrawideband (UWB) is subjected to interference from licensed users although it consumes lower power. Wavelet packet transform is an alternative to Fourier transform with higher flexibility and spectrum utilization. In this paper, a wavelet packet-based transceiver is designed for cognitive UWB to improve robustness against interference from primary users. The proposed transceiver consists of two main components: 1) wavelet packet multicarrier modulation (WPMCM) for data transmission and 2) wavelet packet-based spectrum sensing (WPSS). In the transceiver, the presence of the primary user is sensed via WPSS with adaptive thresholding. Then, the WPMCM signal is transmitted over the detected unoccupied channels. The simulation results show interference reduction due to lower sidelobes level of power spectrum density compared with the Fourier-based system. Significant performance enhancement has been achieved in terms of probability of detection, probability of false alarm, and bit-error rate over UWB channels.

Error concealment using multiple description coding and LIoyd-max quantization

There has been increasing usage of Multiple Description Coding (MDC) for error concealment in non ideal channels. This paper attempts to conceal the error and reconstruct the lost descriptions by combining MDC and LIoyd-max quantizer. At first original image downsampled to four subimages then by using wavelet transform each subimage is mapped to transform domain then descriptions are quantized by LIoyd-max and coded. Since in proposed method wavelet transform is been used, there could be no blocking effect as compared to DCT transform. The results show that average MSE (mean square error) for our proposed method in comparison with DCT method (in other paper) has decreased from 240 to 152 in 0.625 bpp (bit per pixel), from 161 to 107 in 1 bpp and from 96 to 73 in 2 bpp in rate-distortion performance. Therefore, this method is suitable for low capacity channels. By losing descriptions, the obtained image is still in good quality (subjective evaluation and PSNR values) as compared to a method which is DCT and MDSQ (multiple description scalar quantization).

Multi-criteria load balancing decision algorithm for LTE network

Long Term Evolution (LTE) is a cellular system designed to support user mobility even at high speed. When a mobile user moves from one cell to another cell during active service session, handover technology is employed to transfer its connections from the previous cell to the new cell for effective Load balancing of the entire network. However, handover of a mobile user therefore is a serious factor when considering user mobility management in LTE network. This is to provide services with stringent tolerance with best handover latency to enhance network quality. Presently, an optimised load balancing mechanism in LTE network is still left as open issue as far as 3GPP is concerned. For optimum use of network resources, an effective load balancing framework is required before handover process could be beneficial. In this work, we provided the detail framework requirement of multi-Criteria Load balancing Decision Algorithm in LTE. We captured our criteria using multiple parameters for effective mobility load balancing. The scheme allows for an optimized load distribution effect in the network by adjusting handover margin at the appropriate time. Our results provide better performance in terms of the network throughput and network load distribution index when compared with network without proper load balancing scheme.

Investigation of error concealment using different transform codings and multiple description codings

Investigation of Error Concealment Using Different Transform Codings and Multiple Description Codings There has been increasing usage of Multiple Description Coding (MDC) for error concealment in non-ideal channels. A lot of ideas have been masterminded for MDC method up to now. This paper described the attempts to conceal the error and reconstruct the lost descriptions caused by combining MDC and lapped orthogonal transform (LOT). In this work LOT and other transforms codings (DCT and wavelet) are used to decorrelate the image pixels in the transform domain. LOT has better performance at low bit rates in comparison to DCT and wavelet transform. The results show that MSE for the proposed methods in comparison to DCT and wavelet have decreased significantly. The PSNR values of reconstructed images are high. The subjective evaluation of image is very good and clear. Furthermore, the standard deviations of reconstructed images are very small especially in low capacity channels.

Investigation on channel capacity enhancement for MIMO-OFDM in fading channels using hybrid water filling and nash algorithm

In this competing wireless communication system, channel capacity is one of the important considerations in promising reliable communication over wireless medium. The demand for channel capacity is increasing from time to time due to the increase of wireless network users. The combination of Multiple Input Multiple Output and Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is a convincing solution to enhance the capacity of different fading channels. However, the channel capacity is still limited by the use of power allocation algorithm. The existing channel capacity is dependent on Water Filling power allocation algorithm. In this paper, a hybrid algorithm of Water Filling and Nash algorithm is proposed and is applied to revise the power allocations to the channels. The proposed method has considered Rayleigh, Rician and Nakagami fading channels in the simulations. The results have shown that the channel capacity is increased significantly in different fading channels by using the proposed method compared to the existing water filling algorithm. In the future, researchers may focus on the improvement of the channel capacity in terms of power allocation method.

Investigation on decoding failure probability in erasure network coded channels

In this paper wireless communications network is considered to transmit source information to destination. N number sources transmitting data to a destination receiver, through M relays nodes by employing random linear network coding (RLNC). Two methods of failure decoding probability on performance of wireless communication are explained and discussed in this paper. The major parameter that will impact on the decoding probability of RLNC are quantity of relays, a finite field size, and erasure probability. The comparison of two old bounds method (Seongs approach) and new bounds method (from Khans approach) is explored in this research. Simulation results, shows that new bounds method on probability of decoding failure having better simulation results compared to old bound method. It is also concluded that calculating the bounds of the decoding probability is an easy method to analyze failure decoding probability compared to Chiasserinis approach method which is based on network coded matrix.