Ali Hakan Ulusoy

Channel estimation using short training sequences

The estimation of the impulse responses of time-variant mobile radio channels is a challenging issue in mobile communication systems. For CDMA systems, it is generally assumed that the receiver knows the corresponding spreading sequences. A maximum likelihood channel estimation method, which uses the known spreading sequences together with short training sequences, is considered for synchronous CDMA systems.

Iterative Least Squares Channel Estimation in Frequency Selective CDMA Systems

Multiple access interference (MAI) is the main factor affecting the performance of channel estimation techniques for code division multiple access (CDMA) systems. Although, several multi-user channel estimation algorithms have been proposed to mitigate MAI, these algorithms require high computational complexities. In this paper, we address the problem of least squares (LS) mobile channel estimation at high channel efficiency that requires a short training sequence along with the spreading sequences. Then, we employ an efficient iterative method based on conjugate gradient (CG) algorithm to reduce the computational complexity of the estimation method. Computer simulations illustrate that the proposed method performs almost identical to the exact LS estimate for reasonable training lengths.

An Overview of Energy-Efficient Cloud Data Centres

The designers of computing systems have interested on the improvements of computing performance that are driven by the demand of consumer, business, and scientific applications. However, further growth of computing performance has started to be limited due to the increasing energy consumption of cloud data centres as a result of carbon dioxide footprints and overwhelming electricity bills. Therefore, the designers of computing systems have started to improve the energy efficiency. In this study, we present an overview of energy efficient design of cloud virtualized data centres to guide future design and development efforts.

Impact of impulsive noise on millimeter wave cellular systems performance

Millimeter wave (mmWave) communication is a resplendent technology for the Fifth Generation (5G) systems. This outdoor cellular system, 5G, is expected to provide internet connections 40 times faster and with at least four times more coverage worldwide than the current 4G Long Term Evolution (LTE) wireless communications standard. However, mmWave communication system performance could be degraded severely by the non-Gaussian Impulsive Noise (IN) and this will create a cruel task to mitigate such harmful effect and modify the impairments in the system. In this paper, blanking and clipping filters are utilized in order to enhance the capability of the communication system in suppressing IN. The problem of receiver design for large antenna arrays at both the base station and mobile station in the presence of IN is modeled using Gaussian mixture model. The results reveal that the proposed algorithms of blanking and clipping are able to minimize the bit error rate.