Sharif Digital Repository

Massive-MIMO and C-RAN are the two technologies which will be among most important parts of fifth generation (5G) stsrems. They will find widespread uses in future years. However, data transfer rate between these two technologies is a challenging problem. Also channel estimation is crucial in massive-MIMO systems. In this research, the problem of estimating the channel and the problems with the data transfer rate between these two technologies are investigated. We propose using 1-bit quantizers to solve the rate problem and also an algorithm with perfect performance in aspect of error rate is proposed. The mentioned algorithm is implemented on GPUs, which are available at C-RANs and resulted... 

Channel estimation is one of the fundamental challenges in every communication system and different algorithms have been proposed to deal with it. Obviously, type of a communication channel is an important factor in choosing the appropriate method for channel estimation. Sparse channels are one kind of them that occur in many real-world applications such as wireless communication systems. In addition, emergence of a new means in signal processing to deal with sparse signals, known as Compressed Sensing(CS), paved the way for their extensive usage in many applications including sparse channel estimation.On the other hand, one of the most fundamental problems in sparse signal recovery using CS... 

Millimeter-wave (mmWave) communication systems exhibit large bandwidth and severe channel attenuations. To maintain the received signal-to-noise ratio on an acceptable level, mmWave systems use large antenna arrays and directional beamforming at both transmitter and receiver. The existence of many antenna elements, however, challenges traditional approaches for pilot transmission and channel estimation wherein the number of pilots linearly scales up with the total number of transmit antennas. For instance, for the uplink channel estimation with a constant coherence interval, adding more antennas to the users comes at the expense of a linear penalty on the number of users, which can... 

Channel equalization is a crucial part of the OFDM communications protocols, which in turn requires channel estimation. Pilot-based methods are one the most popular channel estimation approaches in OFDM systems. The pilot signals are generally classified as orthogonal and nonorthogonal pilots. Orthogonal pilots can better estimate the channels and are widely used in communications systems. The number of orthogonal pilots is proportional to the number of transmitters. Therefore, utilizing orthogonal pilots are not amenable for the increasing number of users in communications systems and the emerging of new technologies such as Massive-MIMO employing a large number of antennas. Consequently,... 

Telecommunications industry along energy industry will be among striking elements in improving next-generation lifestyle. With the growth of wireless communications at the heart of telecommunications industry, cellular networks as an inevitable part of our daily life, have been around as a fertile research field for both academia and industry. With the upcoming Heterogeneous Networks (HetNets), these researches are revisited to new horizons. After these shift paradigms,the proposed solutions, mostly fall into the category of network densification in terms of antenna per (active) user. Based on the strategy chosen to densify the network, we face two broad approaches: 1) Centralized... 

Wireless communications often requires accurate knowledge of the underlying channel be­ tween transmitter and receiver which leads to channel estimation problem. Wireless chan­ nels are mostly multipath channels and have sparse impulse responses in time domain. One popular method in this field is to estimate the channel using training symbols. Also, Orthog­ onal Frequency Division Multiplexing (OFDM) and Multiple-Input Multiple-Output OFDM (MIMO-OFDM) systems are two popular and widely used systems. Since in training-based channel estimation methods some resources which can be utilized for data transmission is used for the channel estimation process, decreasing the number of pilots or... 

Increasing need to high rates of transmission through radio channels is a challenging problem in wireless communications. Simple implementation and high spectral efficiency of OFDM system turned it into a suitable choice to meet this need. Accurate estimation of the communication channel has a significant impact on performance of Orthogonal Frequency Division Multiplexing (OFDM) systems. Conventional methods of channel estimation are not able to exploit the inherent sparsity of the channel that is due to sparse distribution of scaterrers. On the other hand, Compressed Sensing (CS) is getting attention in variety of aspects such as communications, recently.CS-based channel estimation exploits... 

Recently, there has been much interest in sparse channel estimation, i.e. recovering a channel which has much less non zero tabs than its length. These channels have been observed in underwater and broadband wireless channels. In the last few years methods available to estimate these channels have used sparse structure information to improve the estimates. However, these methods are vulnerable to noise and interference. In other words, these methods do not use channel posterior information obtained from the received signal and this is detrimental to the estimator performance. In order to solve these problems in this thesis, motivated by CoSAMP algorithm which is a sparse signal processing... 

Cooperative communications have been introduced to combat degrading effects of fading in wireless networks and attracted much attention recently. This technique provides distributed spatial diversity that enables energy-efficient transmission of information from source nodes to destination nodes via intermediate relay nodes. Most existing protocols, detection techniques and optimization methods in cooperative networks assume that perfect channel state information is available. While in practical situations, the estimates of the channels may only be known and for acquiring such knowledge, a fraction of power and bandwidth have to be spent for channel estimation using pilot symbols. In this... 

In this thesis, we investigate the problem of OFDM channel estimation exploiting channel sparsity. Due to the sparse nature of the scattering objects, most of wireless multipath channel have a sparse impulse response. Therefore it is possible to use the methods in the field of sparse signal processing for the purpose of estimating such channels for better accuracy, and efficient spectrum usage.
First of all the problem of OFDM channel estimation using scattered pilots is stated. Then the so-called IMAT methods together with the other sparse signal processing methods are used for the purpose of estimating channel nonzero taps. Furthermore, since efficient use of spectrum in... 

Recently, sparse channel estimation, i.e. recovering a channel which has much less non zerotaps than its length using a known training sequence, has been a major area of research in the field of sparse signal processing. It can be shown that on the one hand, the underlying unique structure of such channels will make the possibility of estimating the channel taps with the extreme performance, i.e. achieving the Cram´er-Rao bound of the estimation. On the other hand, with an appropriate use of this structure, computational complexity of the receiver (both channel estimator and equalizer) can be reduced by an order. For achieving these goals in this thesis, firstly we have proposed an... 

Due to extension of wireless networks, indoor positioning service becomes more important in new generations of WLAN networks. Complicated nature of indoor propagation channel decreases the quality of localization service in urban area. To overcome this problem, we surveyed characteristics of indoor radio channels and proposed methods to specify channel parameters to reduce its effect on positioning error. For this purpose, we introduce some super resolution methods and compare their precision and ability to implement on hardware. Among all of them, Matrix Pencil is selected and its mathematical functions are analyzed and stated in numerical algorithms and basic units. In implementain phase,...