Abstract
Channel estimation is a challenging and timely issue for the 3rd Generation Partnership Project (3GPP) standardized low power wide-area network technology named narrowband Internet of Things (NB-IoT). Channel estimation is crucial to achieve extended radio coverage, energy efficiency, coherent detection, and channel equalization for signal repetition dominated NB-IoT uplink transmission. The NB-IoT inherits simplified baseband radio frequency processing, physical channels, reference signal structure, and numerology from existing Long Term Evolution (LTE) systems to save power and costs. Thus, channel estimation methods extensively employed in LTE systems may not be applied to the NB-IoT uplink systems. In this paper, efficient discrete cosine transform type-I (DCT-I)-based transform-domain channel estimation approaches are proposed by modifying the original definition of DCT-I. The proposed methods can mitigate the problems experienced in the discrete Fourier transform (DFT)-based channel estimation, such as signal aliasing error, and border effect. The proposed approaches improve channel estimation precision by reducing signal distortion from the high-frequency region in the time-domain when non-sample-spaced path delays exist in multipath fading channels. Signal aliasing error experienced from the virtual subcarriers is also minimized with the anticipated schemes. The proposed methods are applied on simple least squares (LS) estimates in time-domain to eliminate estimation noise. The viability of the proposed estimators is verified as compared to the conventional LS, DFT-based de-noising LS, and standard DCT-I based methods through extensive numerical simulations. Based on the numerical simulations, the proposed estimators show better mean square error and bit error rate performances than their competitors in extremely low coverage conditions.
Highlights
N ARROWBAND Internet of Things (NB-IoT) is an emerging and extremely narrowband cellular-based low power wide-area network (LPWAN) technology [1]–[5], which was introduced by the 3rd Generation PartnershipProject (3GPP) as a representative technology in release13 for providing massive connectivity of geographically distributed IoT devices to the Internet
The simplified radio frequency (RF) baseband processing, and numerology from the current Long Term Evolution (LTE) standards can be reused for deploying narrowband Internet of Things (NB-IoT) tehnology with in-band and guard-band modes of operation
One physical resource block (PRB) which corresponds to 180 kHz system bandwidth from LTE carrier will be shared for in-band and guard-band operations
Summary
N ARROWBAND Internet of Things (NB-IoT) is an emerging and extremely narrowband cellular-based low power wide-area network (LPWAN) technology [1]–[5], which was introduced by the 3rd Generation Partnership. The background of the DCT-I based transform-domain CE for NB-IoT uplink systems is provided . We propose efficient NDMRS-aided low-complexity CE approaches by modifying the original definition of DCTI for LTE-based NB-IoT uplink transmission. Efficient DCT-I based transform-domain CE approaches are proposed by modifying the original definition of DCT-I to effectively estimate the channel response as well as equalize and detect the repeatedly transmitted NB-IoT UE signals. The system performance of the proposed estimators is evaluated and compared with the state-of-art methods in terms of channel mean square error (MSE) and bit error rate (BER) through rigorous link-level computer simulations following the 3GPP release-15 uplink NB-IoT standards [23], [24]. Euclidean norm will be represented with the operators E[·], and · , respectively
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