Decision Directed Channel Estimation Aided OFDM Employing Sample-Spaced and Fractionally-Spaced CIR Estimators

Abstract—In this letter we characterize the substantial difference between two channel estimation approaches, namely the sample-spaced (SS) and the fractionally-spaced (FS) channel impulse response (CIR) estimators. The achievable performance of decision-directed channel estimation (DDCE) methods employing both the SS- and the FS-CIR estimators is analyzed in the context of an OFDM system. The performance of the two estimation methods is compared and it is shown that the DDCE scheme employing the Projection Approximation Subspace Tracking (PAST)-aided FS-CIR estimator outperforms its SS-CIR estimator-based counterpart. Index Terms—Multiuser OFDM, decision directed channel estimation, impulse response estimation SDMA

Enhanced Channel Estimation Based On Basis Expansion Using Slepian Sequences for Time Varying OFDM Systems

The Channel estimation in OFDM has become very important to recover the accurate information from the received data as the next generation of wireless technology has very high data rate along with the very high speed mobile terminals as users. In addition the fast fading channels, ICI, multipath fading channels may completely destroy the data. Also it is required to use less complex method for estimation. We are proposing the method which compares the number of techniques and gives the results in BER Vs SNR graphs. The LS estimation technique is less complex as compared to MMSE estimation but gives fails in accuracy. Using Prolate function we can reduce the complexity in calculation of parameters. If compared with state of art approach where the complexity is O(N)3, the complexity using Prolate function is O(N)2.The function depends upon maximum delay and maximum Doppler frequency spread thus parameter calculation is reduced. The technique dose not calculate particular channel characteristics. Slepian sequences utilizes the bandwidth as the sharp pulses replace the regular rectangular pulses which causes spectral leakage and thus ICI. The simulation of BER Vs SNR using CP and UW with and without Prolate is proposed that increases spectral efficiency with reduced calculations replacing rectangular pulses by Slepian pulses which increase energy concentration by Sharpe pulses thus reduction in inter carrier interference caused by multipath fading. DOI: 10.17762/ijritcc2321-8169.150513

Channel estimation in massive MIMO systems

Last years were characterized by a great demand for high data throughput, good quality and spectral efficiency in wireless communication systems. Consequently, a revolution in cellular networks has been set in motion towards to 5G. Massive multiple-input multiple-output (MIMO) is one of the new concepts in 5G and the idea is to scale up the known MIMO systems in unprecedented proportions, by deploying hundreds of antennas at base stations. Although, perfect channel knowledge is crucial in these systems for user and data stream separation in order to cancel interference. The most common way to estimate the channel is based on pilots. However, problems such as interference and pilot contamination (PC) can arise due to the multiplicity of channels in the wireless link. Therefore, it is crucial to define techniques for channel estimation that together with pilot contamination mitigation allow best system performance and at same time low complexity. This work introduces a low-complexity channel estimation technique based on Zadoff-Chu training sequences. In addition, different approaches were studied towards pilot contamination mitigation and low complexity schemes, with resort to iterative channel estimation methods, semi-blind subspace tracking techniques and matrix inversion substitutes. System performance simulations were performed for the several proposed techniques in order to identify the best tradeoff between complexity, spectral efficiency and system performance

MIMO signal processing in offset-QAM based filter bank multicarrier systems

Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft