Radio resource management

Michael Fitch

BT Technology, Services and Operations

December 2017

What I’d like to talk about

▪ The need for RRM (briefly),

▪ Some research:

A technique for choosing the best radio access technology

(RAT) from a set of options, using fuzzy logic and multiple-

attribute decision making (MADM)

Simulation results using video and FTP traffic over licensed and

unlicensed spectrum,

▪ Key findings and planned further work

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Acknowledgment

The research reported in this presentation was conducted by the Speed-5G project that receives

funding from the European Commission H2020 programme under Grant Agreement N: 671705.

The European Commission has no responsibility for the content of this presentation.

The need for Radio Resource Management

▪ RRM will increase spectrum utility if spectrum and Radio Access

Technology (RAT) type can be flexibly matched with link

requirements, for example by:

Making most use of unlicensed spectrum,

Using high frequencies and low powers for short ranges.

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RRM has to do the following:

▪ Work within the constraints of spectrum regulation,

▪ Decouple RAT from spectrum type:

I assume that all future auctioned licensed spectrum will be

technology neutral (as is most current licensed spectrum)

Unlicensed spectrum normally uses WiFi, but LTE is also

possible:

LAA uses licensed and unlicensed spectrum, where a licensed anchor is

used for signalling and high QoS data, and unlicensed carriers are used for

other data. LBT is used,

LTE-U has the control plane over licensed and all data over unlicensed and

does not use LBT and so is not used in Europe,

MuLTEfire operates LTE entirely in unlicensed spectrum (and uses LBT).

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Software defined radio is a key enabler for RRM

RRM functions on the control plane and steers

the MAC towards RAT type and spectrum to use

for each session,

The KPI collector keeps track of KPIs per session,

The Spectrum Manager is the available portfolio

of spectrum with policies for its use.

RAT / spectrum selection: an RRM algorithm using

fuzzy logic and MADM

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New application

to be established

Out of context

suitability levels

(fuzzy logic)

In context

suitability levels

(MADM)

Short term RAT attributes

(eg from reference

signals)

Context components

(eg power, velocity)

Medium and long term

RAT attributes and

MADM parameters

(eg cost, range, weights)

Decision: rank

RATs and choose

best one

Step 1

Step 2

Step 3

With this implementation the UE connection manager is

assumed to be steered by the RRM

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Design requirements

▪ Context-awareness needed to exploit the various context

components associated with:

Applications (e.g. QoS requirements)

UE (e.g. battery level and velocity)

Network (e.g. operator strategies and regulation rules),

▪ User-driven fast decisions (e.g. switch to traditional RATs out of

5G coverage),

▪ Network assistance to provide UEs with the relevant information

and offer flexibility to the network manager.

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Inputs to RAT decision process

▪ X applications with various requirements

𝐴𝑥 (1<𝑥<𝑋)

▪ K available RATs 𝑅𝐴𝑇𝑘 (1<𝑘<𝐾)

▪ S subscription profiles 𝑃𝑠 (1<𝑠<𝑆)

▪ Various context components

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Step 1: Estimate out of context suitability level 𝑆𝑘,𝑥𝑜𝑐 for

each RAT / application pair using fuzzy logic

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FLCRAT

parameters

𝑆𝑘,𝑥𝑜𝑐

RAT parameters can be RSRP, time waiting in buffers, packet loss rate etc

and may require some pre-processing such as averaging. The FLC runs a set

of inference rules to combine multiple inputs of multiple levels, to a single output.

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-20 -19 -16 -15 RSRP/dBm

Degree of membership

Low Medium High

𝑆𝐿𝑇𝐸,𝑣𝑖𝑑𝑒𝑜𝑜𝑐0.8 0.9

Degree of membership

Low High

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Example input RAT parameter Example output

Step 2: Use Multi-Attribute Decision Making to include

context and also to include the 𝑆𝑘,𝑥𝑜𝑐 from step 1

(a) Construct decision matrix Dx whose elements 𝑑𝑘,𝑚𝑥 denotes the performance of

RATk in terms of the mth attribute:

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𝐷𝑥 =

(b) Derive a normalised matrix 𝐷𝑥 whose elements 𝑑𝑘,𝑚𝑥 are determined as:

𝑑𝑘,𝑚𝑥 =

𝑑𝑘,𝑚𝑥 /max

𝑘𝑑𝑘,𝑚𝑥

min𝑘

𝑑𝑘,𝑚𝑥 /𝑑𝑘,𝑚

𝑥

for benefit attributes (eg QoS/QoE and range)

for cost attributes (eg cost and power)

RAT QoS/QoE Cost Power Range

RAT1 𝑆1,𝑥𝑜𝑐 Cost1 Power1 Range1

• • • • • • • • • •

RATk 𝑆𝑘 ,𝑥𝑜𝑐 Costk Powerk Rangek

• • • • • • • • • •

RATK 𝑆𝐾,𝑥𝑜𝑐 CostK PowerK RangeK

Step 3: Apply weights and choose best RAT

(the weights are adjusted according to operator policy)

(c) Determine the in-context suitability levels by multiplying by weights

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= 𝐷𝑥 ∗ 𝑊𝑥𝑠

𝑊𝑥𝑠 =

(d) Select the kth RAT that maximises the in-context suitability levels

depending on x application and subscription level s

𝑘∗ 𝑥, 𝑠 = argmax𝑘

𝑆𝑘,𝑥𝑖𝑐,𝑠

𝑆1,𝑥𝑖𝑐 ,𝑠

• •

𝑆𝑘 ,𝑥𝑖𝑐 ,𝑠

• •

𝑆𝐾 ,𝑥𝑖𝑐 ,𝑠

𝑤𝑥 ,𝑄𝑜𝑠𝑠

𝑤𝑥 ,𝑐𝑜𝑠𝑡𝑠

𝑤𝑥 ,𝑝𝑜𝑤𝑒𝑟𝑠

𝑤𝑥 ,𝑟𝑎𝑛𝑔𝑒𝑠

Use-case for testing

▪ X = 2 applications:

Interactive video with 100ms maximum latency and max frame loss = 0.1

FTP as on-off process where each ‘on’ consumes a fraction ρ of the capacity of

the in-use RAT with loose QoS requirements

▪ K = 3 RATs

LTE: small cells operating in licensed band

WLAN: APs operating in unlicensed band

LBT: small cells sharing WLAN band on listen before talk

▪ S = 2 subscription profiles

Gold which is flat rate

Bronze which is limited credit

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K = LTE, X = video

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- RSRQ = reference signal received quality

- T_Sched = time packets wait in buffer before

being transmitted

K = WLAN, X = video

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- SINR = signal to interference plus noise ratio

- T_ACK = time packets wait in buffer before

being successfully transmitted (ie acknowledged)

- Drop_R = rate of dropped packets due to overloaded

MAC or unsuccessful re-transmissions

K = LBT, X = video

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- RSRQ = reference signal received quality

- T_Access = time packets wait in buffer before

accessing the channel

- NACK_R = the ratio of NACKs out of the HARQ-ACK

feedback values

Step 2, add the in-context attributes to form the Dx and

𝐷𝑥 matrices

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RAT QoS/QoE Cost Power Range

LTE 𝑆𝐿𝑇𝐸 ,𝑣𝑖𝑑𝑒𝑜𝑜𝑐 High High Large

WLAN 𝑆𝑊𝐿𝐴𝑁 ,𝑣𝑖𝑑𝑒𝑜𝑜𝑐 Low Medium Small

LBT 𝑆𝐿𝐵𝑇 ,𝑣𝑖𝑑𝑒𝑜𝑜𝑐 Low High Small

RAT QoS/QoE Cost Power Range

LTE High High High Large WLAN High Low Medium Small

LBT High Low High Small

Dvideo =

DFTP =

Derive the normalised matrix 𝐷𝑥 whose elements 𝑑𝑘,𝑚𝑥 are determined as:

𝑑𝑘,𝑚𝑥 =

𝑑𝑘,𝑚𝑥 /max

𝑘𝑑𝑘,𝑚𝑥

min𝑘

𝑑𝑘,𝑚𝑥 /𝑑𝑘,𝑚

𝑥

for benefit attributes (eg QoS/QoE and range)

for cost attributes (eg cost and power)

Step 3: Apply weights and choose best RAT

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= 𝐷𝑣𝑖𝑑𝑒𝑜 ∗ 𝑊𝑣𝑖𝑑𝑒𝑜𝑠

𝑊𝑣𝑖𝑑𝑒𝑜𝐺 =

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑄𝑜𝑠𝐺 = High

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑐𝑜𝑠𝑡𝐺 = High

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑝𝑜𝑤𝑒𝑟𝐺 = High

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑟𝑎𝑛𝑔𝑒𝐺 = High

𝑊𝑣𝑖𝑑𝑒𝑜𝐵 =

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑄𝑜𝑠𝐵 = High

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑐𝑜𝑠𝑡𝐵 = Low

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑝𝑜𝑤𝑒𝑟𝐵 = High

𝑤𝑣𝑖𝑑𝑒𝑜 ,𝑟𝑎𝑛𝑔𝑒𝐵 = High

𝑆𝐿𝑇𝐸 ,𝑣𝑖𝑑𝑒𝑜𝑖𝑐 ,𝑠

𝑆𝑊𝐿𝐴𝑁 ,𝑣𝑖𝑑𝑒𝑜𝑖𝑐 ,𝑠

𝑆𝐿𝐵𝑇 ,𝑣𝑖𝑑𝑒𝑜𝑖𝑐 ,𝑠

And another diagram like this for x = FTP that is

very similar.

Then finally the best k RAT for x application and

s subscription is

𝑘∗ 𝑥, 𝑠 = argmax𝑘

𝑆𝑘,𝑥𝑖𝑐,𝑠

Video test set-up

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QoE parameters used were:

1. Peak signal to noise ratio (PSNR): measures similarity based on a frame-by-frame

comparison.

2. Structural Similarity (SSIM) index: focuses on the structural information loss, to

which our eyes are strongly sensitive.

Sequence was 2-min Big Buck Bunny sequence (16+ million views on Youtube).

It is encoded with H264 (Main Profile, L4) at 1080p @24fps.

Model is ultra-dense environment

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1. Single macro-cell overlaid by various buildings.

2. A small-cell randomly deployed in each room on top of an AP.

3. Small-cells are dual-access i.e., share licensed bands with macro (co-channel)

and unlicensed bands with existing WLAN based on listen-before-talk (LBT).

Simulation assumptions

▪ Single cell scenario (with interference and pathlosses taken

from ultra-dense environment)

▪ Gold and Bronze video sessions with one FTP transfer initially

on WLAN.

▪ Fraction of used capacity by FTP (ρ) used to load the WLAN (so

FTP stays on WLAN)

▪ May choose LTE / WLAN (offload) / LBT (sharing) for video and

switch between them

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Results for PSNR

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Results for SSIM

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QoE of Bronze user with WLAN load at 40%

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Frame ID = 5900

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Offloading

Sharing

Offloading

plus sharing

Key findings and further planned work

▪ Gold user stayed on LTE the whole time,

▪ Bronze user: significant gains due to utilisation of unlicensed

band:

Offloading better at low WLAN loads, sharing better at high

WLAN loads,

Proposed approach switches efficiently between both

options, 12dB improvement in PSNR,

▪ Further planned work:

More RATs (e.g. mm-wave) and more applications (e.g.

adaptive video streaming and massive IoT),

Real-world trials.

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Background regulatory information

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Use of spectrum

▪ Spectrum is loosely categorised in terms of licensed, lightly licensed, or

unlicensed

Strictly though, it is the operator who is licensed to operate equipment that uses

the spectrum.

▪ The licence can be Spectrum Access (technology neutral) or Technology

Specific.

Examples of TS bands are the 1800MHz that is specified for 3G and LTE only,

and the low power GSM (LPGSM) band at 1900MHz that is specified for 2G

and LTE only

The trend is towards SA, and all future auctions are assumed to be for SA

spectrum

▪ The licence specifies limits for transmit power, channel widths, in-band and out-

of-band unwanted emissions, specifies TDD / FDD and can include additional

ETSI or 3GPP specifications

▪ Different equipment in the same system is licensed in different ways

In LTE for example, the base-stations operate on a licensed basis but the UEs

operate on an unlicensed basis because they are owned by individuals and

they move around

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Use of spectrum

▪ The holder of a spectrum licence has sole use of that spectrum

It enables the holder to manage interference and offer controlled QoS to its

customers. It allows the highest transmit powers of all licence options and

hence has the longest range

It is also expensive, and is best reserved for high QoS high value services

▪ Lightly licensed equipment is a sensible option only for small planned

deployments

The regulator keeps a record of locations of BSs, and there is an annual fee for

every piece of equipment. It is shared spectrum so QoS guarantees are not

possible.

Medium powers are used so the range is medium (a few km). An example of its

use is TV Whitespace. It is not a good option for planned or mass unplanned

deployments like LTE or WiFi

▪ Unlicensed equipment can be used by anyone

Is free, is best effort, and needs a form of contention management that works

across equipment from different operators.

It is low power and hence works only over short ranges (eg indoors)

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