Millimeter Wave MIMO Systems for 5G Access Networks

By | October 14, 2014

Guest post by Faris Alfarhan*

Cellular NetworkConventionally, millimeter wave (mmW) frequency bands have been either largely overlooked or treated solely as real estate for wireless backhaul and personal indoor networks. That is mainly due to higher atmospheric attenuation loss, penetration losses, and increased absorption and scattering in rainy conditions. However, recent measurements indicate good outdoor short range coverage – of 200 meters on average – when using directive antenna beams, even when radio line of sight conditions are not met [1-3]. The propagation characteristics of mmW bands vary considerably depending on whether LOS or NLOS conditions are present. Since mmW signals experience low diffraction due to their small wavelength, LOS signals propagate in conditions similar to free space (a path loss exponent of 2 on average). NLOS signals, on the contrary, experience more significant losses and hence a pathloss exponent of 5.7 on average [3]. However, the NLOS pathloss exponent is significantly reduced when directing the Tx and Rx antenna beams towards each other. In order to overcome the increased pathloss at mmW frequencies, directional beamforming or beamsteering is used to generate narrow beams towards users. Since the required antenna size is inversely proportional to the operating frequency, mmW antenna arrays could encompass as much as 64-256 antenna elements at the base station and 4-12 elements on a mobile device. For example, the required antenna element length is about 0.5 cm at 28 GHz,whereas it is about 20 cm at 700 MHz. Figure 1 shows measurement results for the maximum coverage distance of a mmW systems operating at 28 GHz as a function of the pathloss exponent and the combined Tx-Rx antenna gains, where acceptable coverage is deemed to have an SNR of 10 dB and higher.

Maximum coverage distance at 28 GHz and a Tx power of 30 dBm, as a function of the combined Tx-Rx antenna gains and the path loss exponent n.

Figure 1: Maximum coverage distance at 28 GHz and a Tx power of 30 dBm, as a function of the combined Tx-Rx antenna gains and the path loss exponent n [3].

Maximum coverage distance at 28 GHz and a Tx power of 30 dBm, as a function of the combined Tx-Rx antenna gains and the path loss exponent n [3].

This opens the door for potential use of mmW bands for small cells in wireless access networks to boost network capacity, while macro cells provide blanket coverage in lower UHF bands. The attractive part about mmW bands is the abundance of communication bandwidth. It is expected that governments could make as much as 100 GHz of spectrum available for telecommunications in such bands. While the research community is increasingly active in designing mmW transceivers and MIMO systems, it is envisioned to have operational mmW access networks by 2018. While many have jumped to conclude that mmW systems will be the main technology of 5G networks, I like to believe that it is more of an important component that contributes to the 5G network vision rather than 5G itself. Leaving the industrial aspects of mmW systems aside, this article identifies the main challenges that mmW MIMO systems face in making it a reality.

1- Outdoor to indoor penetration loss

mmW signals do not penetrate brick, concrete, and heavily tinted glass. Penetration losses for brick and concrete walls range between 7-35 dB. This reinforces the need for separate wireless indoor solutions to cover indoor hotspots. However, this doesn’t eliminate the use of mmW indoors, as mmW signals could penetrate dry walls and clear glass with relatively low losses. Distributed indoor mmW antenna systems could also be used in addition to other complementary wireless standards suitable for indoor deployment.

2- MIMO system and transceiver design complexity

From a multipath diversity point of view, mmW channels are often sparse in delay spread, spatial selectivity, and angle spread; the number of significant multipath components is considerably lower when compared to UHF channels, which results in highly correlated multipath fading channels of low rank and high spatial correlation, especially in LOS and near LOS conditions. This typically places a constraint on the potential of the implemented MIMO algorithm. Techniques such as maximal ratio combining (MRC) ideally require high rank channels of low fading correlation between the channel’s multipath components. However, minimum mean squared (MMSE) or zero-forcing based MIMO algorithms could be still bring significant beamforming gains in mmW channels, provided there is a large number of antenna elements [4].

Beamforming and steering could be performed digitally or via analog circuitry. Digital beamforming is performed by multiplying the digital information symbols by digital beamforming weights before converting the symbols to analog signals. Digital beamforming has the versatility of selecting beamforming weights of precise amplitudes and phases at the price of higher computational complexity. However, digital beamforming requires a separate RF chain consisting of an analog to digital converter (ADC) and a power amplifier for each antenna element. Hence, the amount ADCs and amplifiers scales linearly with the number of antenna elements in such case. And to make matters worse, ADCs are more power hungry and costly when designed to work in mmW bands. This effectively makes digital beamforming highly impractical for use in mmW transceivers. The alternative is to use analog directional beamforming via electronic phase shifters coupled with an RF path sharing transceiver architecture. Instead of using an RF chain for each antenna element, a limited number of RF chains could be shared across multiple antenna elements. The signals of the multiple antenna elements could be separated by orthogonal code multiplexing, where per-element signals are combined into a single RF, baseband, ADC path. This eliminates the need for multiple RF chains and significantly reduces the power consumption at the cost of increasing the communication bandwidth by the coding rate [4]. The shortfall of using analog beamforming though is the limitation of only using a subset of phase shifts, while keeping a constant amplitude for all analog signals resulting in a constant envelope signal.

3- Mobility

Mobility is always a challenge in short range cellular networks. However, it is even more challenging to handle in mmW MIMO systems, as there is no guarantee for locked accurate beamforming on moving targets. Since Doppler shifts increase linearly as a function of speed and the operating frequency, mmW signals received at moving targets experience higher Doppler spreads. Thus, pilot based channel estimation must be reported more frequently to guarantee accurate beamforming. This however means an increased amount of overhead that is also proportional to the number of antenna elements in a massive MIMO system, and an increased rate of computational complexity to process the beamforming weights in time. Such stringent mobility constraints may mean that highly mobile user cannot be served at mmW frequencies.

In general, even in the absence of mobility, TDD implementations are favoured for massive MIMO systems in order to exchange the large amount of channel state information (CSI)frequently with less overhead. CSI is gathered in TDD systems by relying on the reciprocity between the downlink and uplink channels. However, in practice, this requires calibration of the RF chains of the receiver and transmitter, which are generally not reciprocal. That is because the communication channel doesn’t only consist of the air interface, but also includes the antennas, RF mixers, filters, ADCs, and power amplifier.

The bottom line is: though considerable challenges exist, mmWave massive MIMO arrays designed for small cell geometries could potentially bring orders of magnitude in capacity gains in wireless access networks.


Faris is wireless systems engineer in the research and specifications team at InfoVista. His domain of interest and expertise include radio access network design and optimization, performance simulations, and advanced technologies.



[1] Rappaport, T.S.; YijunQiao; Tamir, J.I.; Murdock, J.N.; Ben-Dor, E., “Cellular broadband millimeter wave propagation and angle of arrival for adaptive beam steering systems (invited paper),” Radio and Wireless Symposium (RWS), 2012 IEEE , pp.151,154, Jan. 2012

[2] Ben-Dor, E.; Rappaport, T.S.; YijunQiao; Lauffenburger, S.J., “Millimeter-Wave 60 GHz Outdoor and Vehicle AOA Propagation Measurements Using a Broadband Channel Sounder,” Global Telecommunications Conference (GLOBECOM 2011), 2011 IEEE, pp.1,6, Dec. 2011

[3] Rappaport, T.S.; Shu Sun; Mayzus, R.; Hang Zhao; Azar, Y.; Wang, K.; Wong, G.N.; Schulz, J.K.; Samimi, M.; Gutierrez, F., “Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!,” Access, IEEE , pp.335,349, 2013

[4] Swindlehurst, A.L.; Ayanoglu, E.; Heydari, P.; Capolino, F., “Millimeter-wave massive MIMO: the next wireless revolution?,” Communications Magazine, IEEE , vol.52, no.9, pp.56,62, Sept. 2014