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


Wireless communication using very-large multiple-input multiple-output (MIMO) antennas is a new research field, where base stations are equipped with a very large number of antennas as compared to previously considered systems. In theory, as the number of antennas increases, propagation properties that were random before start to become deterministic. Theoretical investigations with independent identically distributed (i.i.d.) complex Gaussian (Rayleigh fading) channels and unlimited number of antennas have been done, but in practice we need to know what benefits we can get from very large, but limited, number of antenna elements in realistic propagation environments. In this study we evaluate properties of measured residential-area channels, where the base station is equipped with 128 antenna ports. An important property to consider is the orthogonality between channels to different users, since this property tells us how advanced multi-user MIMO (MU-MIMO) pre-coding schemes we need in the downlink. We show that orthogonality improves with increasing number of antennas, but for two single-antenna users there is very little improvement beyond 20 antennas. We also evaluate sum-rate performance for two linear pre-coding schemes, zero-forcing (ZF) and minimum mean squared error (MMSE), as a function of the number of base station antennas. Already at 20 base station antennas these linear pre-coding schemes reach 98% of the optimal dirty-paper coding (DPC) capacity for the measured channels.

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    • "Massive MIMO [1]–[5] is an emerging technology in wireless access. By using a large number (tens to hundreds) of antennas at the base station, and serving many users in the same time-frequency resource, massive MIMO can improve the spectral and transmit-energy efficiency of conventional MIMO by orders of magnitude [6]–[9], and simple signal processing schemes are expected to achieve near-optimal performance [10]–[12]. The basic premise of massive MIMO is that, as confirmed by several experiments [13]–[16], the propagation channel has a large number of spatial degrees of freedom. "
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    ABSTRACT: Massive MIMO can greatly increase both spectral and transmit-energy efficiency. This is achieved by allowing the number of antennas and RF chains to grow very large. However, the challenges include high system complexity and hardware energy consumption. Here we investigate the possibilities to reduce the required number of RF chains, by performing antenna selection. While this approach is not a very effective strategy for theoretical independent Rayleigh fading channels, a substantial reduction in the number of RF chains can be achieved for real massive MIMO channels, without significant performance loss. We evaluate antenna selection performance on measured channels at 2.6 GHz, using a linear and a cylindrical array, both having 128 elements. Sum-rate maximization is used as the criterion for antenna selection. A selection scheme based on convex optimization is nearly optimal and used as a benchmark. The achieved sum-rate is compared with that of a very simple scheme that selects the antennas with the highest received power. The power-based scheme gives performance close to the convex optimization scheme, for the measured channels. This observation indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF chains and performing antenna selection using simple algorithms.
    IEEE Transactions on Communications 07/2015; DOI:10.1109/TCOMM.2015.2462350 · 1.99 Impact Factor
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    • "Upon increasing the number of antennas at the eNB, the channel correlation decreases, and the measured sumrates approach their theoretical limits. When the eNB employs 20 antennas, about 98% of the sum-rate of the ideal DPC scheme is achieved for a pair of single-antenna aided UEs by the ZF or RZF TPCs [29]. • Effects of the propagation environment [28]: Considering realistic environments, both a 128-antenna cylindrical and a linear array are employed at the eNB [28]. "
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    ABSTRACT: The escalating tele-traffic growth imposed by the proliferation of smart-phones and tablet computers outstrips the capacity increase of wireless communications networks. Furthermore, it results in substantially increased carbon dioxide emissions. As a powerful countermeasure, in the case of full-rank channel matrices, MIMO techniques are potentially capable of linearly increasing the capacity or decreasing the transmit power upon commensurately increasing the number of antennas. Hence, the recent concept of Large-Scale MIMO (LS-MIMO) systems has attracted substantial research attention and been regarded as a promising technique for next-generation wireless communications networks. Therefore, this paper surveys the state-of-the-art of LS-MIMO systems. Firstly, we discuss the measurement and modeling of LS-MIMO channels. Then, some typical application scenarios are classified and analyzed. Key techniques of both the physical layer and network layer are also detailed. Finally, we conclude with a range of challenges and future research topics.
    IEEE Communications Surveys &amp Tutorials 07/2015; DOI:10.1109/COMST.2015.2425294 · 6.81 Impact Factor
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    • "Due to their simplicity and optimality in massive MU- MIMO systems [10], we examine the performance MF and ZF linear precoding techniques. 1) MF Precoding: The MF precoder (also known as a matched beamformer (MBF) and maximum ratio transmission (MRT)) is the most computationally inexpensive precoding technique, allowing the design of many inexpensive antennas ideal for massive MIMO systems. MF precoding in a MU- MIMO system aims at maximizing the received power at each user while neglecting the effects of interference to the other co-scheduled users. "
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    ABSTRACT: In this paper we examine a number of deployment issues which arise from practical considerations in massive multiple-input-multiple-output (MIMO) systems. We show both spatial correlation and line-of-sight (LOS) introduce an interference component to the system which causes non-orthogonality between user channels. Distributing the antennas into multiple clusters is shown to reduce spatial correlation and improve performance. Furthermore, due to its ability to minimize interference, zero forcing (ZF) precoding performs well in massive MIMO systems compared to matched filter (MF) precoding which suffers large penalties. However, the noise component in the ZF signal-to-noise-ratio (SNR) increases significantly in the case of imperfect transmit channel state information (CSI).
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