Sharif Digital Repository

Identification of modulation and space-time block code (STBC) is an important task of receivers in applications such as military, civilian, and commercial communications. Here, we consider multiple-input multiple-output (MIMO) systems. We propose two methods for STBC identification when the modulation is known. We also introduce a method for joint identification of code and modulation. Additionally, we present an enhanced zero-forcing (ZF) equaliser to improve the separation between the features of different classes. Higher order cumulants are used as the statistical features. In the first method of STBC identification, after the proposed equalisation, received data samples are segmented,... 

Schizophrenia is a severe brain disease that influences the behaviour and thought of person. These effects may fail in achieving the expected levels of interpersonal, academic, or occupational functioning. Although the underlying mechanism is not yet clear, the early detection of schizophrenia is an attractive and challenging research area. There are differences in brain connections of patients and healthy people. This study presents a new computer-aided diagnosis (CAD) method to diagnose schizophrenia (SZ) patients from normal control (NC) people by using the rest-state functional magnetic resonance imaging (R-fMRI) data. fMRI data has a huge dimension, and extracting efficient features is... 

Device-to-device (D2D) communication improves spectrum efficiency (SE) and increases system capacity. Heterogeneous networks comprise macrocell and several small cells, such as picocells and femtocells, where femtocells are more efficient. In cooperative communications, one or several additional nodes help to send data from source to destination to improve the quality of service (QoS). Network coding (NC) in cooperative networks can extend data rate and coverage area of D2D communication. The purpose of this article is to minimize power consumption of transmitting nodes during network-coded cooperative D2D transmission to reduce the interference on co-channel transmissions. In this study, we... 

The aim of this paper is to present a non-linear statistical model to fit and forecast the signal-to-interference plus noise ratio (SINR) in two-tier heterogeneous cellular networks which consist of macrocells and femtocells. Since in these networks the number and locations of femtocell base stations (FBS) are variable, SINR forecasting can be useful in some areas such as power control and handover management. So far, linear autoregressive (AR)models have commonly been used in forecasting the received signal strength (rss) inmacrocellular networks.However,ARmodelling results in highmean square error (MSE)when data are non-linear. This paper focuses on SINR which takes into account signal... 

In this study, the problem of variable bit rate (VBR) video traffic prediction is addressed. VBR traffic prediction is necessary in dynamic bandwidth allocation for multimedia quality of service control strategies. Autoregressive (AR) models have been widely used in VBR traffic prediction where the least mean square (LMS)-based methods were utilised for parameter estimation. However, they are ineffective when the traffic is dynamic in nature. In this study, using the Brock, Dechert, and Scheinkman (BDS) test, it is shown that the video traffic is non-linear. Kernel is an efficient tool to convert non-linear data into linear one in a higher-dimensional space. The kernel LMS (KLMS) method is... 

The current state of device-to-device (D2D) communication in the presence of cellular network addresses two major challenges of interference as well as throughput inadequacy. Specifically, a D2D communication underlaying fractional frequency reuse (FFR) cellular network exhibits rather high interferences due to higher occurrence of band crossing within a shared spectrum. However, due to the considerable impact of D2D communications on spectral efficiency and system capacity, the remedy for those issues may include efficient techniques of interference mitigation and average spectral efficiency maximization. In this paper, we propose a resource block (RB) allocation scheme to reduce the... 

The aim of this study is to improve the performance of two-tier macro/femtocell networks using a power control approach. In wireless networks, power control plays an important role in improving a number of performance parameters such as co-channel interference and outage probability reduction, throughput increasing, and power saving. This study explores the evolution of centralised power control algorithm based on femtocell base station (FBS) clustering and predicted signal-to-interference-plus-noise ratio (SINR) of users. To reduce the computational complexity of centralised algorithm, dense deployed femtocells are considered in different clusters. In this case, femtocells inside one... 

This study presents an efficient handoff algorithm for heterogeneous networks comprising macrocells, microcells, picocells, and femtocells. The proposed algorithm is based on call admission control (CAC) for selecting target base station (BS) from a list of neighbouring candidate BSs, as well as using the technique for order of preference by similarity to ideal solution (TOPSIS) as decision method. The introduced algorithm takes into account multiple criteria including measured received signal strength (RSS) and signal-to-interference-plus noise ratio (SINR), predicted RSS and SINR, and number of free resource blocks of neighbouring BSs. With the use of TOPSIS, neighbouring BSs are ordered... 

The current state of device-to-device (D2D) communication in the presence of cellular network addresses two major challenges of interference as well as throughput inadequacy. Specifically, a D2D communication underlaying fractional frequency reuse (FFR) cellular network exhibits rather high interferences due to higher occurrence of band crossing within a shared spectrum. However, due to the considerable impact of D2D communications on spectral efficiency and system capacity, the remedy for those issues may include efficient techniques of interference mitigation and average spectral efficiency maximization. In this paper, we propose a resource block (RB) allocation scheme to reduce the... 

The vision of advanced long-term evolution (LTE-A) project is set to ultimate increase of network capacity in heterogeneous networks (HetNets). In HetNets with small cell configuration, a considerable majority of user devices is eventually connected to the macrocell base station (MBS), while small base stations (BSs), such as femtocell access points (FAPs), are still without any user. This results in unbalanced load and reduces the data rate of macrocell user equipment (MUE). In this paper, a method is proposed for load balancing among FAPs, while desired throughput is achieved. The proposed method uses the estimated received signal strength from different BSs and adjusted pilot signals.... 

Heterogeneous networks (HetNets) provide the demand for high data rates. In this study, we analyze the coexistence of femtocells and device-to-device (D2D) communication with macrocells. Interference management and decreasing energy consumption are two important issues in HetNets. To this end, we propose an efficient fractional frequency reuse (FFR)-based spectrum partitioning scheme to reduce the cross-tier interference. We also propose to use different optimization problems for resource allocation in different tiers. For this purpose, an energy efficient optimization problem is applied to D2D user equipment. Further, an optimization problem based on the spectral efficiency, i.e.,... 

Device-to-Device (D2D) communication technology, under the standardization of third generation partnership project and a component of the evolving fifth generation architecture, is mainly aimed to increase system capacity and data rate via providing direct communications between end devices without the use of routing data through the network. Apart from the attracting features, due to the resource sharing between cellular user equipment (CUE) and D2D user equipment (DUE) in such communications, an efficient algorithm for resource and power allocation to DUE, especially for mobile users is necessary to maintain the performance. The current paper introduces a joint mode algorithm for mobile... 

Heterogeneous networks (HetNets) provide the demand for high data rates. In this study, we analyze the coexistence of femtocells and device-to-device (D2D) communication with macrocells. Interference management and decreasing energy consumption are two important issues in HetNets. To this end, we propose an efficient fractional frequency reuse (FFR)-based spectrum partitioning scheme to reduce the cross-tier interference. We also propose to use different optimization problems for resource allocation in different tiers. For this purpose, an energy efficient optimization problem is applied to D2D user equipment. Further, an optimization problem based on the spectral efficiency, i.e.,... 

Attention deficit hyperactivity disorder (ADHD) is a common brain disorder among children. It presents various symptoms, hence, utilizing the information obtained from functional magnetic resonance imaging (fMRI) time-series data can be useful. Finding functional connections in typically developed control (TDC) and ADHD patients can be helpful in classification. The aim of this paper is to present a multifold method for the study of fMRI data to diagnose ADHD patients. In the proposed method, first, by applying the Stockwell transform (ST), we obtain detailed information about the time-series of the region of interests (ROIs) in the time and frequency domains. ST provides information about... 

Sleep study is very important in the health since sleep disorders affect the productivity of individuals. One of the important topics in sleep research is the classification of sleep stages using the electroencephalogram (EEG) signal. Electrical activities of brain are measured by EEG signal in the laboratory. In real-world environments, EEG signal is also used in portable monitoring devices to analyze sleep. In this study, we propose an efficient method for classification of sleep stages. EEG signals are examined by a new model from autoregressive (AR) family, namely logistic smooth transition autoregressive (LSTAR) to study sleep process. In contrast to the AR model, LSTAR is a non-linear...