Conference Paper
Linear PreCoding Performance in Measured VeryLarge MIMO Channels.
DOI: 10.1109/VETECF.2011.6093291 Conference: Proceedings of the 74th IEEE Vehicular Technology Conference, VTC Fall 2011, 58 September 2011, San Francisco, CA, USA
Source: DBLP

Article: Linear Precoding Based on Truncated Polynomial Expansion  Part I: LargeScale SingleCell Systems
[Show abstract] [Hide abstract]
ABSTRACT: Largescale multiuser multipleinput multipleoutput (MIMO) techniques have the potential to bring tremendous improvements for future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal nonlinear precoding are solved moreorless automatically by enlarging system dimensions. The computational precoding complexity will, however, still grow with the system dimensions. For example, the closetooptimal regularized zeroforcing (RZF) precoding scheme cannot be applied in largescale MIMO systems, because its computation involves the inversion of a large matrix. Motivated by the high performance of RZF, we propose to replace the matrix inversion by a truncated polynomial expansion (TPE), thereby obtaining a TPE precoding scheme with greatly reduced computational complexity. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission (MRT) and more advanced RZF. Using random matrix theory, we derive a deterministic expression for the asymptotic signaltointerferenceandnoise ratio (SINR) achieved by TPE precoding in largescale MIMO systems. Furthermore, we provide a closedform expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed peruser rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signaltonoise ratio (SNR).10/2013;  [Show abstract] [Hide abstract]
ABSTRACT: Massive multipleinput multipleoutput (MIMO) techniques have been recently advanced to tremendously improve the performance of wireless communication networks. However, the use of very large antenna arrays at the base stations (BSs) brings new issues, such as the significantly increased hardware and signal processing costs. In order to reap the enormous gain of massive MIMO and yet reduce its cost to an affordable level, this paper proposes a novel system design by integrating an electromagnetic (EM) lens with large antenna array, termed the EMlens enabled MIMO. The EM lens has the capability of focusing the power of an incident wave to a small area of the antenna array, while the location of the focal area varies with the angle of arrival (AoA) of the wave. Therefore, in practical scenarios where the arriving signals from geographically separated users have different AoAs, the EMlens enabled system provides two new benefits, namely energy focusing and spatial interference rejection. By taking into account the effects of imperfect channel estimation via pilotassisted training, in this paper we analytically show that the average received signaltonoise ratio in both the singleuser and multiuser uplink transmissions can be strictly improved by the EMlens enabled system as compared to conventional systems without the EM lens. Furthermore, we demonstrate that the EMlens enabled system makes it possible to considerably reduce the hardware and signal processing costs with only slight degradations in performance. To this end, two complexity/cost reduction schemes are proposed, which are smallMIMO processing with parallel receiver filtering applied over subgroups of antennas to reduce the computational complexity, and channel covariance based antenna selection to reduce the required number of radio frequency chains.IEEE Journal on Selected Areas in Communications 12/2013; 32(6). · 3.12 Impact Factor  [Show abstract] [Hide abstract]
ABSTRACT: This paper introduces filter bank multicarrier (FBMC) as a potential candidate in the application of massive MIMO communication. It also points out the advantages of FBMC over OFDM (orthogonal frequency division multiplexing) in the application of massive MIMO. The absence of cyclic prefix in FBMC increases the bandwidth efficiency. In addition, FBMC allows carrier aggregation straightforwardly. Selfequalization, a property of FBMC in massive MIMO that is introduced in this paper, has the impact of reducing (i) complexity; (ii) sensitivity to carrier frequency offset (CFO); (iii) peaktoaverage power ratio (PAPR); (iv) system latency; and (v) increasing bandwidth efficiency. The numerical results that corroborate these claims are presented.02/2014;
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.