The document discusses various aspects of millimeter wave (mmWave) technologies and their applications in wireless communication networks, particularly in ultra-dense environments. It covers topics such as channel characteristics, beamforming techniques, interference management, and user association strategies in the context of mmWave communication. Additionally, it explores the challenges posed by blockages, mobility, and resource allocation in mmWave networks.

1. 1
By Eduardo Castañeda
Radio Resource Management for
Millimeter Wave & Massive MIMO

2. 2
The mmWave Channel
Directional antennas compensate
path loss (common
assumption)
LoS (beam alignment) + NLoS
(tracking), both functions of the
length of the link (d) 
in/outdoor
Dominant LoS strong
shadowing + outage
Cluster multipath structure, small
number of clusters, <10
typically, (sparse - low rank
channel)
SINR: array pattern, beamwidth,
directivity gain, side/back lobe
gain
Spatio-temporal directivity: AoD
and AoA knowledge, inst. &
statistics
𝑛𝑊 log2 1 + SINR : wideband
increase spectral noise
density
𝒅
𝒏
𝒏

3. 3
The mmWave Channel
Blockage refers to high penetration loss due
to obstacles and cannot be solved by
increasing the power.
Indoor covergare > outdoor coverage
NLoS/LoS propagation laws for modeling links
Deafness occurs when the main lobes at both
transmitter and receiver do not point to
each other.
Narrow beams reduce inter-beam
interferences and performance is noise
limited - like (outdoor). Tx-Rx beam
mismatch rapidly degrades performance
It’s mitigated by searching alternative beams
or spatial directions. (overhead, codebook
size, complexity)
𝝉 T-𝝉

4. 4
Heterogeneous Bands
Millimeter waves can be used for
high data rates.
Microwave can be used for control
and signaling, since they provide
more reliability. Those services
require low rates.
Robust services over microwaves,
e.g., broadcasting and network
synchronization.
Decoupling Control/User planes, or
UL in microW and DL in mmW
Fall-back tradeoff: sending control
messages over mm or
microwaves.
Swtiching (avoiding) bands with min
(max) RSSI/RSRP/RSRQ
(received signal strength indicator,
power,quality)  distance and Tx
power
6GHz 28GHz 72GHz
39GHz
Multipath + NLoS
EV

5. 5
Ultra Dense Networks
Characteristics
Cellular technology is roaming +
reuse ( OFDMA, frequency reuse
and resource partitioning )
Coverage (LoS for short-range &
NLoS for outdoor), low power and
offloading
Enhanced capacity: bandwidth,
directivity (sector/beamwidth
optimization), less interference
Backhaul

6. 6
Resource and Interference Management
Scheduling/userassociation
• UEs < RF chains
• Coherent time/
bandwidth time-freq
allocation
• RSS, QoS, load, etc.
• Non-uniform UE
distribution
• Bias for load balancing tier-
level (HetNets)
• UL-DL asymmetry
• Complexity vs optimality
tradeoff, deployment-
based performance
Beamforming
• Channel Covariance
spatial allocation based
on 2nd order statistics
• Analog beamforming:
spatial resources to the
best UEs
• UL-DL channel reciprocity
 pilots
• Beam selection and
tracking (codebooks)
• Even IEEE 802.11ac TDD
requires feedback for
frame sync!
Interference
• Centralized ICI
coordination for multi-tier
nets
• On-demand interference
management
• Omnidirectional control
channels: broadcasting,
sync, estimation
• HetNets: users, QoS,
power, loads, antennas
• Centralized vs distributed
schemes: tradeoff

7. 7
Beamforming SchemesCSIT
• Open loop: channel
sounding + codebooks
• Closed loop: i)
Feedback BF matrix
w/wo compression. ii)
feedback CSI
• Compressive sensing
and sparcity
• Massive MIMO: long
term CSIT is needed OutdoorBF
• Analog: phase shift +
constant gain;
available commercialy!
• Digital: SVD, ZF, MF
• Hybrid: sub-array,
full-array, and more
architectures
• Hybrid is massive
MIMO oriented
• ~10-200 m coverage
in field trials
WLAN-WPAN
• Sector level sweep:
omni ↔ directional
• Beam refiment phase
(SINR based)
• Beam tracking:
continous channel
estimation
• Multipath defines #
layers per UE
• Alignment overhead -
Throughput tradeoff

8. 8
Hybrid Bemaforming / Combining Architectures
Z. Gao, L. Dai, D. Mi, Z. Wang, M. A. Imran, and M. Z. Shakir, “MmWave massive-MIMO-based wireless backhaul for
the 5G ultra-dense network,” IEEE Wirel. Commun., vol. 22, no. 5, pp. 13–21, 2015.

9. 9
Massive MIMO: performance f(SINR), BF, interference
𝑅 𝑘,𝑗 = 1 −
𝜏
𝑇
log2 1 + SINR 𝑘,𝑗
SINR 𝑘,𝑗
𝑍𝐹
=
1 − 𝑣𝑗 𝑔 𝑘,𝑗
2
SNR𝑗/𝑣𝑗
𝜂 + 𝜎2 𝑔 𝑘,𝑗
2
SNR𝑗 + 𝑙∈𝒥:𝑙≠𝑗 𝑔 𝑘,𝑙
2
SNR 𝑙 + 𝑙∈𝒥 𝑞(𝑘) :𝑙≠𝑗
1 − 𝑣𝑙 𝑔 𝑘,𝑙
2
SNR 𝑙 /𝑣𝑙
SINR 𝑘,𝑗
𝑀𝐹
=
𝑔 𝑘,𝑗
2
SNR𝑗/𝑣𝑗
𝜂 + 𝑙∈𝒥 𝑔 𝑘,𝑙
2
SNR 𝑙 + 𝑙∈𝒥 𝑞(𝑘) :𝑙≠𝑗
𝑔 𝑘,𝑙
2
SNR 𝑙 /𝑣𝑙 SNR𝑗 =
𝑃𝑗
𝑁0
𝑣𝑗 =
𝑆𝑗
𝑀𝑗
Symbols per slot for UL
pilots (overhead)
Symbols per coherent block
user
BS
Number of BS antennas
(# of RF chains)
Streams at BS j
Spatial
load
𝑔 𝑘,𝑗
2
Pathloss and
shadowing
𝜂
BS power
normalizer
𝒥 𝒥 𝑞(𝑘)
Set of BSs
BSs with same
Pilot sequence q(k)
1/𝜎2
UL SNR
Tx SNR at BS j
Omnidirectional
Antennas: microWave
𝑔 𝑘,𝑗
2
= 𝑔 𝑘,𝑗
2
∙ 𝑓(AoD, AoA)
Directional
Antennas: mmWave
Data Rate

10. 10
Access Mechanisms PHY-CC
Synchronizationandcell
search
• Primary and secondary
signals / Sync signals and
cell ID
• Microwaves use
omni/semi-directional
beams, but mmWaves
require full-directional
beams
• SINR can be modeled
according to directivity
(geometry) Systeminformation
extraction
• Parameters: Bandwidth,
freq. Bands, Tx antennas,
access scheme
• Sinlge or multiple bands
• Dedicated mmWave
channel for signaling and
estimation ~28GHz
• On-demand spatial sync:
beams
Access
• Contention based
(collition domain) or
contention-free based
access (dedicated CCH)
• V2V, WLAN, WPAN, e.g.
802.11ad (55-68 GHz) and
802.11.15.3
• Example: backoff due to
deafness  resources
waste
• Directivity  #beams vs
overhead : tradeoff

11. 11
Mobility ManagementHandover
• Handovers in dense
deployments may be
frequent
• Limitations of RSS,
local load neglected
• Beam mismatch 
triggers HO
• Dedicated backhaul
resources for the BSs
in soft or hard HO
Noise+Delay
• Increase of
overhead/delay due
to reassociation,
beam refiment and
CSI acquisition
• Cloud cell
(centralized arch.) 
low latency
• Phase noise and
Doppler effect
increases with 𝑓𝑐
Robustness
• UE association with
multiple BS.
• Dual connectivity -
association but one
Tx per UE  reduce
complexity
• Dynamic cell setting
+ user centric RRM
[ Athanasiou2015 ]

12. 12
Metrics for Cloud Cell FormationUEtrafficdemand
• QoS
• Throughput vs
Fairness
• Association to
several groups,
classess, BSs
• Combinatorial
problems and
coupled SINRs BS-UEChannel
• Voronoi regions
based on RSRP /
RSSI not appropriate
if load or QoS are
considered
• Serving area defined
in the angular domain
DoA
• Complexity of the
objective functions
BSsloads
• Based on the number
of antennas
• Based on the number
of users per Tx
• Based on total bits to
be delivered
• Energy efficiency
becomes relevant if
BSs are switched
On/Off

13. 13
Offloading: User Density + Traffic
Distance-based matching
BS-UE is not effcieint for
HetNets + mmWaves:
power disparity and load
imbalance per transmitters
Cell boundaries are not clear
in hetnets operating in
mmWaves  HO beyond
coverage area
1. D2D: proximity services
2. Small cells: operate at high freq.,
e.g. HomeNB. 80% of traffic is
indoor!
3. I-WLAN architecture: WiFi + 3GPP
mobile networks

14. 14
Summary
Identified characteristics of the wireless channel in mmWave
Candidate frequency bands for cellular communications and
services
Discussion of several process RM for mmWave:
Scheduling: SINR modeling and parametrization
Beamforming: channel estimation and hybrid architectures
Interference management
Mobility + Handover
Dynamic Cloud Cell formation
Offloading Techniques
14

15. 15
References
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Perspective,” IEEE Trans. Commun., vol. 63, no. 10, pp. 3437–3458, Oct. 2015.
2. S. Kutty and D. Sen, “Beamforming for Millimeter Wave Communications: An Inclusive Survey,” IEEE Commun. Surv.
Tutorials, vol. 18, no. 2, pp. 949–973, Jan. 2016.
3. D. Liu, L. Wang, Y. Chen, M. Elkashlan, K.-K. Wong, R. Schober, and L. Hanzo, “User Association in 5G Networks: A Survey
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Frequencies,” IEEE Commun. Mag., no. January, pp. 202–208, 2015.
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