MIMO and Massive MU-MIMO Wireless Technology

Multiple-input multiple-output (MIMO) is a physical layer technique that pro- vides an increase in spectral efficiency without additional increase in transmit power and/or bandwidth. First proposed for consumer technology in IEEE 802.11n-2009 [47], MIMO technology has been incorporated to virtually all cur- rently utilized wireless systems, which include LTE and LTE advanced [48–50], WiMAX, and IEEE 802.11ac and 802.11ax [51]. The key idea is to utilize multiple

Up to 9 Unique Radio

Paths

Primary Antenna 2 (Mid Band) Primary Antenna 1 (Low/Mid Band)

Diversity Antennas (Rx only) MU-MIMO (Wi-Fi) Primary Antenna 3 (CA) 5 GHz LTE-U

Figure 2.2: Samsung Galaxy S8 utilizes multiple antennas to achieve downlink speeds of 1 Gigabit per second [45, 46].

1995 2000 2005 2010 2015 2020 1 Kbps 1 Mbps 1 Gbps 100 Gbps 100BASE 1000BASE 10GBASE 100GBASE 200GBASE HDMI 1.0

HDMI 1.4a HDMI 2.0

HDMI 2.1

USB 1.0

USB 2.0

USB 3.0 USB 3.1 USB 3.2

802.11b 802.11g 802.11n _802.11ac802.11ax IS-95 W-CDMA HSDPA 802.16e HSPA+LTE LTE advanced

wired

wireless

Figure 2.3: Trends and data rates of modern wired and wireless technology: Slope of the date rate of wireless is higher than that given by wired technology. antennas at the transmitter and/or receiver simultaneously to achieve higher throughput and/or improving reliability. Since these additional antennas allow multiple data streams to be utilized independently, in general, MIMO offers sig- nificantly increased throughput compared to single-input single-output system. Fig. 2.2 shows an example of a Samsung Galaxy S8 smartphone, which utilizes multiple antenna simultaneously to achieve maximum speed of 1 Gigabit per second. In addition, the smartphone has two diversity antennas which help to improve reliability.

Fig. 2.3 shows data rates for commonly used wired and wireless systems for consumer technology. We observe that the gap between wired and wireless communications is diminishing, and it is predicted that wireless will eventu- ally provide higher throughput than wired technology [52]. The trend is also reflected in Edholm’s law [52], which states that telecommunications data rates are doubling every 18 months, which is exactly identical to the transistor scaling in Moore’s law.

2.2.1 Massive MU-MIMO

To address the exponential increase in data without simply increasing the power nor allocating more bandwidth, Marzetta proposed a “massive” or large-scale MIMO system where the number of antennas are scaled up even at a greater magnitude [53]. An analysis of scaling the BS antennas to infinity, while keeping the number of user antennas constant, showed that the effect of fading disappears completely. This effect was also known as “wires-in-the-air” [54]. Moreover, in the asymptotic regime simple matched-filter equalization was proved to be optimal (see Section 3.3.4 for a detailed discussion).

The largest difference between massive MIMO and current MIMO is the number of antennas at the BS. Current state-of-the art MIMO standards such as LTE-Advanced [48] and/or IEEE 802.11ax [51] supports up to 8 BS and 8 user equipment (UE), whereas massive MIMO envisions the usage of hundreds or even thousands of antennas while only increasing the UE to the order of tens. Due to the order-of-magnitude increase in the antennas at the BS, massive MIMO is also commonly referred as large-scale MIMO or very-large MIMO [5]. We

time 1 time 2 time 3

(a) Conventional MIMO

time 1 time 2 time 3

(b) Massive MIMO

Figure 2.4: Illustration of conventional MIMO and massive MIMO: Unlike con- ventional MIMO, massive MIMO allows fine-grained beamforming that simpli- fies the UE equalization and data detection procedure.

highlight some of the advantages of massive MIMO:

1. Uplink–Fading is significantly reduced in Massive MIMO: In the uplink (UL), where UE is communicating to the BS, the BS performs equalization and detection on the signals sent by the UE. Although the wireless fading is random due to the propagation environment, combining the received signals coherently significantly reduce fading, and virtually eliminate fad- ing in the asymptotic limit [6]. This phenomena is also known as “channel hardening” [5, 55, 56]. Since fading is reduced significantly, equalization processing can be made simpler at the BS.

2. Downlink–Fine-grained beamforming: In the downlink (DL), where BS is communicating to the UEs, the BS can utilize the additional antennas to perform preprocessing the UE’s data signal. The additional antennas can be used to constructively add the signal directed to each UE increasing the received signal strength, while destructively removing the inter-UE inter- ference. This procedure, known as precoding, can be done in the digital

domain without additional analog circuitry. Precoding couples well with massive MIMO as larger number of antennas provide a greater spatial reso- lution. As a result, precoding provides the UE with its corresponding data at a significantly lower interference compared to existing MIMO systems. Fig. 2.4 shows a the prime difference between conventional MIMO and massive MIMO. The BS can utilize the wireless channel knowledge to per- form much finer beamforming Fig. 2.4(b) compared to that of conventional MIMO Fig. 2.4(a).

3. Reduced power consumption at UE: In the uplink, fading is reduced by fine-grained beamforming at the BS, utilizing the large number of arrays to perform coherent combining. Therefore, the UE can operate at a lower signal-to-noise ratio and hence, reducing transmit signal power. In the downlink, precoding pushes the computational complexity to the BS so that UE only has to perform simple equalization and data detection. This shift of computational burden decreases the hardware cost at the UE due to simpler communication hardware and reduced power consumption.

On top of providing higher link reliability and reduced power consumption at the UE, massive MIMO can provide significantly higher spectral efficiency compared to existing MIMO systems by serving multiple users simultaneously at the same time-frequency resource.

Fig. 2.5 shows how multi-user MIMO can bring significantly improved spec- tral efficiency. In single-user MIMO shown in Fig. 2.5(a), a total of three users are communicating from the BS over three time slots, where we show only for time slot 1. While each UE can have multiple antennas, each UE occupies the whole time slot (blue, green, red) for communication. However, in MU-MIMO

time 1 time 2 time 3

(a) Single-user massive MIMO

time 1 time 2 time 3

(b) Multi-user massive MIMO

Figure 2.5: Illustration of single-user and multi-user massive MIMO: Multi- user massive MIMO can bring significantly increased spectral efficiency over conventional state-of-the-art MIMO technology by serving multiple UEs in the same time-frequency resource.

shown in Fig. 2.5(b), multiple UEs (each with possibly multiple antennas) can be served simultaneously in a same time slot. In the uplink, the BS performs coherent equalization for the UE’s transmit signals; in the downlink, the BS performs precoding for beamforming to remove inter-user interference. Since this procedure can be done on a per-time-slot basis, the MU-MIMO can serve multiple users over multiple time-slots. As shown in Fig. 2.5(b), the three UEs are served in a single time slot, which provides much greater spectral efficiency compared to one UE served for a single-user MIMO.