Conference Paper

# Linear Pre-Coding Performance in Measured Very-Large MIMO Channels.

DOI: 10.1109/VETECF.2011.6093291 Conference: Proceedings of the 74th IEEE Vehicular Technology Conference, VTC Fall 2011, 5-8 September 2011, San Francisco, CA, USA

Source: DBLP

- [Show abstract] [Hide abstract]

**ABSTRACT:**Massive multiple-input multiple-output (MIMO) wireless communications refers to the idea equipping cellular base stations (BSs) with a very large number of antennas, and has been shown to potentially allow for orders of magnitude improvement in spectral and energy efficiency using relatively simple (linear) processing. In this paper, we present a comprehensive overview of state-of-the-art research on the topic, which has recently attracted considerable attention. We begin with an information theoretic analysis to illustrate the conjectured advantages of massive MIMO, and then we address implementation issues related to channel estimation, detection and precoding schemes. We particularly focus on the potential impact of pilot contamination caused by the use of non-orthogonal pilot sequences by users in adjacent cells. We also analyze the energy efficiency achieved by massive MIMO systems, and demonstrate how the degrees of freedom provided by massive MIMO systems enable efficient single-carrier transmission. Finally, the challenges and opportunities associated with implementing massive MIMO in future wireless communications systems are discussed.IEEE Journal of Selected Topics in Signal Processing 10/2014; 8(5):742-758. · 3.30 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**In this paper, resource allocation for multipleinput multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) downlink networks with large numbers of base station antennas is studied. Assuming perfect channel state information at the transmitter, the resource allocation algorithm design is modeled as a non-convex optimization problem which takes into account the joint power consumption of the power amplifiers, antenna unit, and signal processing circuit unit. Subsequently, by exploiting the law of large numbers and dual decomposition, an efficient suboptimal iterative resource allocation algorithm is proposed for maximization of the system capacity (bit/s). In particular, closed-form power allocation and antenna allocation policies are derived in each iteration. Simulation results illustrate that the proposed iterative resource allocation algorithm achieves a close-to-optimal performance in a small number of iterations and unveil a trade-off between system capacity and the number of activated antennas: Activating all antennas may not be a good solution for system capacity maximization when a system with a per antenna power cost is considered.Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on; 01/2012 - [Show abstract] [Hide abstract]

**ABSTRACT:**We consider a multipair decode-and-forward relay channel, where multiple sources transmit simultaneously their signals to multiple destinations with the help of a full-duplex relay station. We assume that the relay station is equipped with massive arrays, while all sources and destinations have a single antenna. The relay station uses channel estimates obtained from received pilots and zero-forcing (ZF) or maximum-ratio combining/maximum-ratio transmission (MRC/MRT) to process the signals. To reduce significantly the loop interference effect, we propose two techniques: i) using a massive receive antenna array; or ii) using a massive transmit antenna array together with very low transmit power at the relay station. We derive an exact achievable rate in closed-form for MRC/MRT processing and an analytical approximation of the achievable rate for ZF processing. This approximation is very tight, especially for large number of relay station antennas. These closed-form expressions enable us to determine the regions where the full-duplex mode outperforms the half-duplex mode, as well as, to design an optimal power allocation scheme. This optimal power allocation scheme aims to maximize the energy efficiency for a given sum spectral efficiency and under peak power constraints at the relay station and sources. Numerical results verify the effectiveness of the optimal power allocation scheme. Furthermore, we show that, by doubling the number of transmit/receive antennas at the relay station, the transmit power of each source and of the relay station can be reduced by 1.5dB if the pilot power is equal to the signal power, and by 3dB if the pilot power is kept fixed, while maintaining a given quality-of-service.05/2014;

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.