Capacity Analysis of IRS-Based UAV Communications With Imperfect Phase Compensation

Al‐Jarrah, Mohammad; Alsusa, Emad; Al-Dweik, Arafat; So, Daniel K. C.

doi:10.1109/lwc.2021.3071059

Cited by 65 publications

(69 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…RIS carried by UAV approach has been proven to improve the performance of the system significantly in nonorthogonal multiple access (NOMA) [8], orthogonal frequency division multiple access (OFDMA) [9] VOLUME xxxx, xxxx and free-space optical (FSO) communication system [10]. The capacity and signal gain after applying the RIS-UAV system has been studied in [11], [12]. In [11], the RIS can be equipped with UAVs to apply certain phase shifts of the incident waves before it is reflected to the receiving UAV.…”

Section: Introductionmentioning

confidence: 99%

“…The capacity and signal gain after applying the RIS-UAV system has been studied in [11], [12]. In [11], the RIS can be equipped with UAVs to apply certain phase shifts of the incident waves before it is reflected to the receiving UAV. It can also be deployed on building walls to reflect radio waves towards specific UAVs in order to improve their received signal gain and enhance the performance of UAVs cellular communications [13].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Aerial Reconfigurable Intelligent Surface-Enabled URLLC UAV Systems

Yin

Do‐Duy

et al. 2021

IEEE Access

View full text Add to dashboard Cite

In this paper, we propose an aerial reconfigurable intelligent surface (RIS) system to support the stringent constraints of ultra-reliable low latency communication (URLLC). Specifically, unmanned aerial vehicles (UAVs) employed onboard RIS panels can act as repeaters to reflect the signal from macro base station (MBS) to all users in the networks. To overcome the dense networks' interference, we propose to use zero-forcing beamforming and time division multiplexing access (TDMA) scheme where each UAV can serve a number of users in its own cluster. We formulate a optimisation framework in terms of UAVs' deployment, power allocation at MBS, phase-shift of RIS, and blocklength of URLLC. Due to highly nonconvex and complex optimisation problem, we first consider to use a deep neural network (DNN) to solve the optimal UAVs' deployment. Then, the optimal resource allocation is proposed to provide the maximal reliability of the considered system with respect to the users' fairness. From the representative numerical results, our proposed scheme is shown to superior to other benchmarks which exhibits the positive impact of aerial RIS in supporting stringent demands of URLLC.INDEX TERMS Ultra-reliable low-latency communications (URLLC), Reconfigurable Intelligent Surface (RIS), Unmanned aerial vehicle (UAV).

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Aerial Reconfigurable Intelligent Surface-Enabled URLLC UAV Systems

Yin

Do‐Duy

et al. 2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…To achieve this goal, the reflected signals from each IRS element should be added coherently by adjusting the phase of each IRS element. Most of the work in the literature demonstrates that increasing the number of reflecting elements improves the signal quality with perfect phase estimation and compensation [2], or when all reflectors have equal phase errors statistics [3], [4]. However, when the statistical properties of the phase error for reflectors are not identical, then increasing the number of reflecting elements does not necessarily improve the link quality.…”

Section: Introductionmentioning

confidence: 99%

“…For example, bit error rate (BER) and outage probability expressions have been derived in the presence of phase errors for a single user IRS under different channel models including LoS [3] and Nakagami-m fading [9]. The achievable capacity for IRS assisted UAV communications under LoS assumption is analyzed in [4]. The impact of the phase quantization errors on the achievable capacity is discussed in [5] where it is shown that phase quantization and phase noise can severely degrade the achievable rate.…”

Section: Introductionmentioning

confidence: 99%

“…As can be noted from the cited literature and the references listed therein, the system performance is typically analyzed while considering that all IRS elements have the same phase error statistics. For example, Al-Jarrah et al [2]- [4] modeled the phase error of each reflecting element as a von Mises random variable with particular concentration factor κ, but the performance is evaluated while assuming that the same κ value is common for all reflecting elements. However, practically this is not the case since phase estimation accuracy may vary for different reflecting elements.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

Jangsher¹,

Al-Dweik²,

Al‐Jarrah³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

<div>This letter considers minimizing the bit error rate (BER) of unmanned aerial vehicle (UAV) communications assisted by intelligent reflecting surfaces (IRSs). By noting that increasing the number of IRS elements in the presence of phase errors does not necessarily improve the BER, it is crucial to use only the elements that contribute to reducing the BER. Consequently, we propose an efficient algorithm to activate only the elements that improve the BER. The proposed algorithm has lower complexity and comparable BER to the optimum selection process, which is an NP-hard problem. The accuracy of the estimated phase is evaluated by deriving the probability distribution function (PDF) of the least-square (LS) channel estimator, and showing that the PDF can be closely approximated by the von Mises distribution at high signal-to-noise ratios (SNRs). The obtained analytical and simulation results show that using all the available reflectors can significantly deteriorate the BER, and thus, elements’ selection is necessary. In particular scenarios, using about 26% of the reflectors provides more than 10 fold BER reduction.</div>

show abstract

Outage probability analysis of multiple intelligent reflecting surface‐assisted single‐input single‐output system with switched diversity

Hindustani

Dixit²,

Sharma

2023

Int J Communication

View full text Add to dashboard Cite

SummaryIn this paper, we have presented the outage probability analysis of multiple intelligent reflecting surface (IRS)‐assisted single‐input‐single‐output (SISO) system with switched diversity schemes. The switched diversity is simpler than the selection combining diversity technique, which can help in reducing the channel estimation overhead. There are two main types of switch diversity schemes, namely, switch and stay combining (SSC) and switch and examine combining (SEC). We consider a SISO wireless scenario in which a single transmitting antenna is sending its message to the receiving antenna with the aid of multiple IRS panels. This communication scenario will arise as a typical application of uplink scenario for future 6G wireless systems. The outage probability (OP) expressions for dual‐IRS‐panel‐aided SSC system and multiple‐IRS‐panel‐aided SEC system are analyzed, respectively, over Rician fading channels. We derive tight approximate OP expressions in closed form for a large number of IRS elements. Further, we derive a simple asymptotic OP for studying diversity order and coding gain. The OP performance with respect to each system parameter is thoroughly explored. Several numerical OP results are presented with corresponding simulated OP results to validate the accuracy of the presented analytical analysis.

show abstract

Capacity Analysis of IRS-Based UAV Communications With Imperfect Phase Compensation

Cited by 65 publications

References 19 publications

Aerial Reconfigurable Intelligent Surface-Enabled URLLC UAV Systems

Aerial Reconfigurable Intelligent Surface-Enabled URLLC UAV Systems

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

Outage probability analysis of multiple intelligent reflecting surface‐assisted single‐input single‐output system with switched diversity

Contact Info

Product

Resources

About