Bassant Abdelhamid

Improved Pilot Sequences Allocation in Massive MIMO Systems

Pilot contamination is one of the main limiting factors for the performance of massive MIMO systems. In this paper, two novel pilot allocation schemes are proposed to mitigate the pilot contamination effect and to enhance the system performance with low complexity of pilot allocation. The pilot assignment schemes are based on dividing the cell into center and edge zones, including uniform N sectors in the edge zone. The overall spectral efficiency of the proposed schemes is maximized over the ratio of center zone radius to the cell radius and the number of scheduled users per cell. Numerical results reveal that the proposed schemes significantly outperform the existing techniques in terms of mitigating the pilot contamination and the spectral efficiency improvement.

Performance evaluation of DVB-S2 and DVB-S2X systems

Recently, Digital Video Broadcasting (DVB) has evolved to improve the spectrum efficiency of current multimedia communications. This paper summarizes the main features and presents the error performance for the second generation of satellite DVB (DVB-S2) utilizing an upgraded MATLAB simulation model. In addition, the paper makes a validation of the developed simulation model by comparing between model results and field measurements. Furthermore, a new version of DVB-S2 (DVB-S2X) is simulated to evaluate its performance. The validity of simulation is tested by comparing with the standard error performance for different modulation and coding (MODCOD). The results show that the actual bit error rate (BER) of the measured DVB-S2 system is higher than those obtained in simulation due to variations in realistic satellite link channel conditions. The simulation results showed that DVB-S2X improves the capacity and the spectral efficiency at very high signal to noise ratio (SNR) by including a new higher order Amplitude Phase Shift Keying (APSK) modulation. Moreover, the new coding ratios for DVB-S2X were found to increase the granularity for more capacity options, and provide certain MODCOD optimized only for linear satellite channel. Finally, the new smaller roll-off factors added to DVB-S2X increase the bitrate capacity for the same bandwidth, but it needs a high complex filter design.

Underlay MIMO cognitive transceivers design with channel uncertainty

Underlay cognitive radio (CR) permits unlicensed secondary users (SUs) to transmit their own data over the licensed spectrum unless the interference from the SUs on the licensed primary user (PU) exceeds an acceptable level. This paper proposes two interference alignment (IA)-based distributed optimization designs for multiple secondary transceivers in underlay cognitive radio case with channel uncertainty. The precoding and power allocation matrices for each SU are either independently or jointly optimized for imperfect channel knowledge to maximize the secondary rates and to control the secondary interference on the primary receiver to be below the acceptable limit that is determined by the primary receiver. Numerical results prove the ability of the proposed methods to support significant secondary rates and to protect the PU from extra interference, within the acceptable primary range, even in presence of channel uncertainty case. In addition, joint optimization design has higher secondary performance than the independent optimization design.

Automatic Image Segmentation of Breast Thermograms

Breast cancer has a great attention worldwide due to the increase of the number of patients, especially women, suffering from this disease. However, breast cancer can be cured if it is detected in its early stages. Breast thermography is a promising screening technique for the early detection of breast cancer. In this paper, an automatic segmentation algorithm for frontal breast thermograms is proposed. The proposed algorithm performance is evaluated using two different databases. The proposed algorithm proves its ability to successfully segment all types of breasts (small, medium, large, asymmetric and flat). Moreover, quantitative measures are computed to verify the capability of the proposed algorithm.

New measurement matrix for compressive sensing in cognitive radio networks

Cognitive radio (CR) is a promising solution for an efficient usage of both wideband and narrowband spectrum. Compressive sensing (CS) paradigm is one of the methods that can assist CR to sense the wideband sparse spectrum using a small number of measurements. The implementation of CS depends on utilising a suitable random or structured measurement matrix. To fully enhance CS performance, the measurement matrix should be a full rank and has a small mutual coherence with the basis matrix. According to these necessities, this study introduces a new measurement matrix called the modified regular parity check (RPC) matrix. RPC matrix that is first designed by Gallager technique suffers from the missing of the previous requirements. Thus, a new algorithm is proposed to convert this matrix to a semi-orthogonal one using the gradient-descent method with a variable step size. The modified RPC matrix has fixed values for all entries regardless of the number of active CR users relative to the maximum expected number of CR users. The results show that the proposed matrix has a low recovery error without increasing the recovery time compared with Gaussian matrix. Moreover, it achieves a higher probability of detection and smaller probability of false alarm.

Mitigation of both doubly selective channels and phase noise effects in OFDM systems

An algorithm is proposed to mitigate both doubly-selective channels and phase noise effects on orthogonal frequency division multiplexing systems by applying an iterative decision-directed feedback method. Moreover, the error propagation is further reduced by using the doubly-selective channel estimates and by reducing the residual phase noise. Simulation results prove that the proposed algorithm significantly achieves a superior performance compared to the perfect decision-directed feedback.

Interference mitigation in heterogeneous networks using Fractional Frequency Reuse

Femtocells are the rising new technology aiming to enhance the indoor coverage for Long Term Evolution (LTE) Advanced networks. However, the interference between the macrocells and femtocells can be a huge obstacle against deploying the femtocells on a large scale. In this paper, two Fractional Frequency Reuse (FFR) deployment schemes (FFR-3 and FFR-6) are being evaluated for heterogeneous networks (HetNets). Moreover, a new scheme is proposed aiming to minimize the interference on the macro-user (MU) in the cell center. Simulation results show that the proposed scheme reduces the outage probability and improves the throughput of the whole network. Furthermore, in the proposed scheme, higher percentages of users are using higher order modulation which improves the total throughput.