coexistence_note.txt

Why 5G needs unlicensed bands?
The Future is Unlicensed: Coexistence in the Unlicensed Spectrum for 5G
1. 5G flexible requirement: ultra dense, scalable, customizable (IoT)
2. flexible UL/DL allocation; finite BW; scalable transmission time interval; op at diff bands
3. 5G needs to use unlicensed bands for its own app; however, there are many other app o this band (existing networks) & lack of coordination
including heterogeneity, mass connectivity, ubiquitous IoT devices
4. use unlicensed spectrum when needed provides (1) flexibility and agility for expanding capacity using (2) cost aspect -> unlicensed bands are free
to use (new unlicensed bands: 7/11 GHz in mm waveband)
5. LTE expands to 5GHz for traffic offloading
6. to satisfy efficiency, scalability, and capacity requirements, need to provide more capacity while not increasing the operational
and capital expenditures
7. so spectrum sharing and oprating in unlicensed bands are essential to 5G objectives.

Problem of heterogeneous app on unlicensed bands
1. need sparse capacity since have sudden increase while; but not as more as possible -> a waste -> need a dynamic mechanism to adapt this
2. micro over-provisioned; small-cell even further (too many heterogeneous) -> so traffic variation
3. unlicensed bands also for massive IoT devices, so high heterogeneous, variable load requirement; massive connectivity (allow for access to
spectrum for innovation)
4. heterogeneous devices have diff protocols/priority setting -> no cooperation -> no fair coexistence

Need coexistence mechanism to cooperate this app
1. cognitive radio/dynamic spectrum access need to provide reliable coex mechanism not to hazard other app in light-licensed/unlicensed Spectrum
2. so why coexistence matters in 5G? -> high heterogeneity, diff app require diff performance measurement (transmission power)
3. the importance of unlicensed bands are getting more and more significant

Challenge: heterogeneous app have diff QoS measurements/priorities
1. challenges in coexistence problem? -> heterogeneous devices use diff protocols -> no coordinate with each other (LTE-U no listen-before-talk, but
Wifi has; LTE-U adapts its offline period when Wifi online)
2. protocols across networks operating in unlicensed bands differ, which may cause unfair sharing schemes or the resources
3. networks should possess adaptability in one of the possible domains: time/freq/code
4. a desirable property for a coexistence scheme should not require substantial modifications to the existing protocols and especially in the terminal hardware.
(should allow update over the air)

Existing solution: Q-learning with constant reward/fixed algo for fixed scenario
1. coex can be done in time/freq/space/code dimensions -> to implement, need flexibility in at least one domains
2. LTE-U has freq domain gap and time domain gap (duty cycle)
Wi-Fi Coexistence with Duty Cycled LTE-U:
1. WiFi has random backoff and listen-before-talk
On The Use of Markov Decision Processes in Cognitive Radar: An Application to Target Tracking:
1. modeling the radar operating environment as a MDP and use RL
2. proposed radar tracking problem based on the perception-action cycle
3. The goal of this application is to enable the radar to learn from offline training data instead of having to perform online optimization during each radar cycle
Multi-agent Reinforcement Learning Based Cognitive Anti-jamming:
1. each WACR needs to avoid the jammer as well as transmissions of other WACRs.
2. addresses such an anti-jamming problem in a multi-agent environment with the goal of finding optimal anti-jamming and interference avoidance policies for the WACRs
3. adopt MARL and Q learning
4. Formalize the underlying POMDP framework assumed in [12] and extend the RL based subband selection policy for anti-jamming to the scenarios inwhich there are multiple
policy-learning WACRs operating in the same spectrum range challenged by a sweeping jammer

Q-Learning Based Fair and Ecient Coexistence of LTE in Unlicensed Band:
1. Q-learning used for an ideal and autonomous selection of an LTE-U operational channel muting duration toward fair and ecient spectrum sharing under a dynamic environment

Schemes: centralized vs decentralized
1. schemes: centralized coordinator -> distribute resources for all devices; decentralized coord -> each operator does its own optimization indep,
share spectrum through observations & own performance

Literature Review
A Context-aware and Intelligent Dynamic Channel Selection Scheme for Cognitive Radio Networks
1. In this paper, a model based on RL is adopted to mimic the cognition cycle to provide context awareness and intelligence among nodes.
2. use Q learning to determine the next channel to switch to in cognitive radio (DSA, second user senses primar user)