There is rising attention in using millimeter wave bands for 5G mobile wireless networks.
Channel models are of utmost importance for measurement campaigns , channel model characterization, system-level simulations , and network access capacity estimations in particular for 5G, which is planned to integrate new frequency bands above 6 GHz. A radio channel model includes the antenna effects (almost all models are of this type), whereas a propagation channel model removes antenna effects and is therefore valid for any antenna type. The latter has the disadvantage of requiring different models for the uplink and downlink channel.
The absolute challenge for a channel model is to have just one channel model with adjustable parameters for all scenarios and propagation effects for the full frequency range from above 6 GHz up to 100 GHz. A practicable approach is to develop a sound collection of 3D channel models for the most likely deployment scenarios [ 28 ] . Identified typical deployment scenarios are
• 3D-urban micro (UMi), such as the open area shown in Figure 6-5 and street canyon shown in Figure 6-6 ), comprising both outdoor-to-outdoor (O2O) and outdoor to indoor (O2I)
• Indoor (InH, such as open and closed offices and the shopping malls shown in Figure 6-7 )
• 3D-urban macro (UMa), comprising O2O and O2I, backhaul for small cells, device-to-device (D2D), and vehicle-to-anything (V2X)
Figure 6-5. 3D-UMi O2O open-area scenario
Figure 6-6. 3D-UMi O2O open-area street canyon scenario
To build a channel model requires data either from measurements in the field or derived from ray tracing. Hence, there have been numerous measurement campaigns over several years, and more are being currently set up, to characterize the millimeter wave communication channel for various specific outdoor and indoor environments.
Using the data sets gathered will then make possible several approaches to addressing challenges like the following:
• The line-of-sight (LOS) and non-line-of-sight NLOS) path loss (PL) model
• Delay and angular spreads
• Shadowing
• Spatial consistency and environment dynamics
• The impact of very large antenna arrays (spherical wave modeling)
• The dual mobility Doppler model for D2D
• The frequency dependency of propagation channel model parameters, due to inadequate available measurement campaign data
• The ratio between diffuse and specular reflections
• Polarization
Channel model parameterization challenges are the estimation of large scale parameters (LSP) like delay spread (DS) , angular spreads (AS) , Ricean K factor (K) and shadow fading (SF) as well estimation of small scale parameters (SSP). Simulation and implementation challenges are complexity, performance and availability.
Figure 6-7. InH shopping mall scenario
Ecosystem stakeholders and projects that have met those challenges and have developed channel models are METIS2020 [ 21 ] , MiWEBA [ 13 ] , ITU-R M, COST2100 [ 8 ] , IEEE 802.11ad [ 20 ] , NYU Wireless [ 25 ] , and Fraunhofer HHI QuaDRIGa [ 19 ] . The 3GPP Spatial Channel Model (SCM) [ 1 ] , WINNER [ 26 ] and ITU-R IMT-Advanced propagation model guidelines [ 17 ] were built on extensive channel-propagation measurement campaigns and apply to frequencies of up to 6 GHz. The IEEE 802.11ad channel model emphasizes the 60 GHz band and an indoor scenario; it is created deterministically, and the parameterization is site-specific. COST 2100 is working on the COST channel model, which exploits measurement campaigns and extracts parameters out of it. QuaDRIGa is modeling MIMO radio channels via ray-tracing for specific network configurations, such as indoor, indoor/outdoor, or outdoor environments implementing a 3D geometry-based stochastic channel model. Currently there are additional ongoing propagation and channel studies at the 5G mmWave Channel Model Alliance (United States, NIST-initiated), mmMagic (Europe), IMT-2020 5G promotion association (China), the ETSI industry specification group on millimeter wave transmission (ISG mWT), and 3GPP.
Many of those channel models are adapted to the 3GPP 3D channel model structure, achieving a good fit with available 3GPP system-level simulation environments. Others model the outdoor wave communication channel, using an approach that is either analytical, statistical, or ray-tracing–based statistical. Figure 6-8 shows an overview of the channel modeling options based on the trade-off between accuracy and simplicity.
Figure 6-8. Channel modeling options
These options for channel modeling can be narrowed down to an extension of the 3GPP 3D model , a map-based model, or something like the hybrid quasi-deterministic model for example from MiWEBA. There is a preference among ecosystem stakeholders for the extension of the 3GPP 3D model by adding features like the following:
• The impact of foliage.
• Atmosphere and rain attenuations as a function of frequency.
• The blockage caused by static and moving objects such as a human body or vehicle. Blockage attenuation generally increases with frequency.
• Spatial consistency, which involves the evolutionary features and the correlation of channels between adjacent UEs or links on the large and small scales, supporting massive MIMO, mobility ,and beam tracking
• Support for large bandwidth and 3D beamforming with antenna arrays consisting of a large number of antennas.
The 3GPP channel model has evolved from the spatial channel model for Multiple Input Multiple Output (MIMO) [ 4 ] over several stages to the most recent 3D channel model for LTE [ 5 ] , all of them for frequencies up to 2.5 GHz. This 3GPP model will be extended to included frequency bands above 6 GHz. 3GPP is conducting a study on a channel model for the frequency spectrum above 6 GHz, approved as RP-151606 “New SID Proposal: Study on channel model for frequency spectrum above 6 GHz” (Samsung, Nokia Networks, 2015), in RAN#69 in September, 2015. From RAN#69 to RAN#70 3GPP TSG RAN identified the status and expectation of existing information about high frequencies, including spectrum allocation, scenarios of interest, measurements, and so on. Beginning in the first quarter 2016, RAN1 will develop a channel model for frequencies up to 100 GHz, taking into account the outcome of RAN-level discussion and discussion in the 3GPP 5G requirement study item (SI). This work will define the additional details of the scenarios of interest required for RAN1 work and will consider the work done outside 3GPP as well as earlier 3GPP work, such as the 3GPP 3D-channel model, as a starting point for the modeling of wireless channels of the high-frequency spectrum for the identified scenarios. Additionally, it will consider the possible implications of the new channel model on the existing 3D channel model for spectrum below 6 GHz.
Research similar to [ 13 ] is exploring the remaining open issues, such as dealing with human body shadowing or reflections caused by moving vehicles or attenuation by dense vegetation in cities. For example, Figure 6-9 is a simplified view of how the channel impulse response amplitude of the line of sight path is strongly attenuated by blockage, whereas the amplitude of reflected paths is not. Further exploration is also needed, and under way, to determine in detail when and how millimeter wave systems are noise or interference limited, and the impact of polarization and greater temporal and spatial channel model resolution.