Transceiver Hardware Impairments in Cognitive Relay Networks

Nalin D. K. Jayakodyⱡ and Khao D. Nguyen*

ⱡInstitute of Computer Science, University of Tartu, ESTONIA

*Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, JAPAN

Estonian CS Theory Days 2016, Tartu, Estonia

29th Jan 2016

Content

• Background: Cognitive Relay Networks

• Contribution/Motivation

• Transceiver Hardware Impairment

• System Model

• Soft Forwarding

• Calculation of LLR

• Simulation Results

• Summary

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• No direct wireless channel

Wireless relay transmission

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Relay node

1st phase 2nd phase

Relay network

The data forwarding algorithm at the relay node is called the Relay Protocol or Relay Scheme

Wireless relay transmission• Relay node supports the wireless transmission even without a direct link.

• Relay also can improve the reliability of the transmission in case the direct link is present.

• Two versions of the received data at B are combined with a data combing algorithm, such as maximal combining.

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1st phase 2nd phase

Amplify and Forward & Decode and Forward

Amplify and Forward

• Constituting one of the simplest and most popular relaying methods, the signal received by the relay is amplified, frequency translated and retransmitted.

• An important design issue related to transparent relaying protocols is the choice of amplification factor in the relay, i.e. constant output power, fixed gain amplification.

Decode and Forward

• Being the prominent counter protocol to the transparent AF protocol, DF detects the signal, decodes it and re-encodes it prior to retransmission. A vast amount of different DF protocols exists today e.g., selective DF, Decode Amplify and Forward (DAF) etc.

• Such regeneration can include sample, demodulating, decoding, re-encoding, re-modulating etc., as well as any joint combination thereof.

Current Bandwidth usage

• Consider two networks

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Network 1:

Network 2:

Relay network: no direct link

Transmit via bandwidth 2

Transmit via bandwidth 1

Bandwidth usage efficiency

• Two networks are sharing same bandwidth?

• Primary network: licensed bandwidth priority

• Secondary network: unlicensed bandwidth limit

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Network 1:

Network 2:

Transmit via the same bandwidth

Interference

Cognitive relaynetwork

Cognitive relay network• Secondary users (SUs) and primary users (PUs) transmit via the same

bandwidth.

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Limit the interferences

Limit transmit power of the SU

Specified applications, such as sensor network, network for disaster area.

A cognitive relay network

Deploy farfrom PUs

Cognitive relay networks• Transmit power limitation and low cost

• Distortions of transceiver will reduce performance

• Transceiver impairment effect should be accounted for analysis

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Limit the interferences

A cognitive relay network

Contributions

• We portray soft information relaying (SIR) protocol for multi-hop cognitive relay networks.

• We provide some simulation results for (achievable) throughput and BER performance of the network with SIR protocol under the impact of hardware impairments.

• For this purpose, an expression is derived for the soft noise variance and equivalent noise variance to reflect the hardware impairments.

• Finally, we present simulation results which show benefits of the SIR scheme compared to hard DF protocol.

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Why soft information relaying?

• The Amplify and Forward (AF) and Decode and Forward (DF) protocols suffer from noise amplification and error propagation, respectively

• In order to combine the advantages of both AF and DF in relay networks, many strategies have been proposed in which soft (reliability) information is transmitted to the destination; this idea is known as soft information relaying (SIR)

• SIR has been shown to be an effective solution which mitigates the propagation of relay decoding errors to the destination

• As the destination decoder works in the probabilistic domain, the soft information relaying (SIR) protocol complies with the decoder’s requirements

• It also improves the reliability of the relay received signal to the destination

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Transceiver hardware impairment

• Main sources of impairment

• Phase noise

• IQ imbalance

• Nonlinearities

• Unify the impacts of transceiver impairments

• Introduce distortion at source and sink

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Each source cause different distortion

Distortion at source Distortion at sink

Transceiver Hardware Impairments

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: Impairment level: AWGN Noise

Received signal model as in Mattaiou et al.:

Simplified general model:

Aggregate

impairment

Variance of impairment-noise-distortion (transmit power P = 1) for difference impairments levels 𝜅2 = [0.08; 0.1275; 0.175]

System Model

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ℎ𝑖 , 𝑔𝑗 − channel co-efficient

𝜂𝑘 ~ 𝒞𝒩 0,𝑁0 , AWGN noise

※ 𝜅𝑟2: Aggregate impairment at R

※ 𝜅𝑑2: Aggregate impairment at D

※ 𝐼𝑃: Maximum transmit power※ All channels are AWGN※ Secondary user※ Primary user

𝛾 =𝐼𝑃𝑁0

Transmit power at S and R

SNR:

𝑃𝑆 = 𝑃𝑅 = 𝐼𝑃

Soft information relaying protocol

is applied at the relay with BPSK

modulation

Relay Protocol

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Ph

ase

1P

has

e 2

Calculate soft-information of the received signal 𝑦𝑆𝑅

SR

SD

Demod.

Hard decisi

onMod.

SoftDemod.

tanh(𝐿/2)

Mod.Soft BPSK

𝒚𝑺𝑹 𝒙𝑹

Soft Information Calculation

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1. LLRs of the received signal

2. Calculate soft bits

3. The relationship between the soft symbol at 𝑥𝑅 and the correct 𝑥𝑅 symbol, is modeled in Li et al. as

where is the soft noise random variable (we can estimate and mean 𝜇 and variance )

Soft Information Modeling

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4. From 3, we can model the received signal at D as

where the equivalent aggregate noise term of the received signal at D from R in the second timeslot.

This equivalent noise distribution has zero mean and variance .

where equals to .

5. The LLR of 𝑦𝑅𝐷 is approximated using the soft noise model as follows

Calculate LLRs at Destination

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6. LLR of 𝑦𝑆𝐷

7. LLR at D

8. Hard decision

Simulations

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Compare the performance of soft information relaying (SIR)

and decode-and-forward (DF) using:

Throughput BER

Target

Parameter Value

Transmit power 𝑃𝑆 = 𝑃𝑅 = 1

Modulation BPSK

Hardware impairment 𝜅𝑅2 = 𝜅𝑅

2 = 𝜅2 ∈ [0,0.175]

Bandwidth 𝐵 = 1 (Hz)

Noise variance 𝜎𝜂2 = 1

Relay protocols DF, hard decisionSIR, soft decision

Result – Achievable Throughput

Throughput performance of the network with soft information relaying when the bandwidth 𝐵 = 1 (Hz), noise variance 𝜎2 = 1 and 𝜅2 =[0, 0.08, 0.175, 0.1275]

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1. Ideal model: throughput increases as the transmit power grows.

2. Impairment model: establish the ceiling throughput cannot increase to infinity.

3. The larger impairment levels, the lower maximum throughput.

Results – BER performance

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1. SIR outperform DF protocol with hard decision

2. BER performance of SIR scheme with 𝜅2 = 0.175 approximately as good as DF with 𝜅2 = 0 and just under SIR scheme with 𝜅2 = 0.175

SIR protocol is efficient in improving system performance

BER performance for the SIR protocol in compared to DF protocol over AWGN channel for ideal transceiver and transceiver model with hardware impairment level 𝜅2 = 0.175

Future: Energy Harvesting Dual-source (DS)

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Single-fixed source (SFS)

Both A and B transmit RF signal to R in the energy harvesting phase

The harvested power at R is 𝐸𝐻

Only one B or A transmits RF signal to R in the energy harvesting phase

The harvested power at R is 𝐸𝐻

Conclusion

• Present a new results in soft information relay network assuming practical imperfect hardware

• Efficient in mitigation of the impact of hardware transceiver impairment compared with DF relaying

• In particular, the BER of the SIR network with hardware impairment level 𝜅2 = 0.175 and the DF protocol with perfect transceiver 𝜅2 = 0 are of the same parity.

• we confirm the fundamental limit of realistic transceiver hardware on the achievable throughput. The maximum throughput is established (ceiling point) even when the transmit power increases to infinity.

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Thank you

References• Y. Li, B. Vucetic, T. F. Wong and M. Dohler, “Distributed turbo coding with soft information relaying

in multihop relay networks,” IEEE Journal on Sel. Areas in Comm., vol. 24, no. 11, pp. 2040–2050, Nov. 2006.

• T. Schenk, RF Imperfections in High-Rate Wireless Systems: Impact and Digital Compensation. Springer Publishing, 2010.

• M. Matthaiou, A. Papadogiannis, E. Bjõrnson, and M. Debbah, “Two way relaying under the presence of relay transceiver hardware impairments,” IEEE Commun. Lett., vol. 17, no. 6, pp. 1136–1139, June 2013.

Acknowledgement This work is supported (in part) by the Norwegian-Estonian Research Cooperation Programme through the grant EMP133, by the Estonian Research Council through the research grants PUT405.