DISTRIBUTED INTERFERENCE AND DELAY AWARE DESIGN FOR D2D COMMUNICATION IN LARGE WIRELESS NETWORKS WITH ADAPTIVE INTERFERENCE ESTIMATION
ABSTRACT
We investigate distributed flow control and powerallocation strategies for delay-aware Device-to-Device (D2D)communication underlaying large wireless networks, where D2Dpairs reuse the resource blocks (RBs) of interior cellular users(CUEs). We consider a distributed D2D power allocation framework,where the D2D pairs individually attempt to maximizetheir own time-average throughput utility, while collectivelyguaranteeing the time-average coverage probability of CUEsin multiple cells. We design a novel method to compute theindividual budget of interference from each D2D pair to CUEsbased on stochastic geometry tools. Then, accounting for timevaryingchannel fading and dynamic D2D traffic arrival, wedesign a distributed interference-and-delay-aware (DIDA) flowcontrol and power allocation strategy based on Lyapunov optimizationand several interference estimation methods. We alsoanalytically derive the performance bounds of D2D pairs andprove that the coverage probability of CUEs can be guaranteedregardless of the interference estimation error at D2D receivers.Finally, simulation results suggest that adaptive interferenceestimation methods are preferred and demonstrate that the DIDAstrategy achieves substantial performance improvement againstalternative strategies.
EXISTING SYSTEM:
The efficacy of D2D communication underlaying cellularnetworks is usually examined with three criteria: throughput,delay, and complexity.Some prior works concerned the throughput metric. To maximize the sum-rate of a CUE-D2D match andsatisfying cellular service constraints, joint resource sharingand power allocation methods were proposed in. Basedon interference pricing methods, two-step power allocationalgorithms were proposed to maximize the throughput of D2Dpairs while protecting the Quality of Service (QoS) of bothD2D pairs and CUEs and to optimize the sum weightedutility of the system in. Combining interference pricingmethods and game theory, resource allocation approaches weredesigned to maximize the D2D sum-rate under the CUE rateconstraints and to guarantee the QoS of both CUEsand D2D pairs. These works only concerned a singleCUE-D2D match, a single cell, or regular cellular networks. Incontrast, we investigate a multi-cell network topology wherethe locations of BSs, CUEs, and D2D transmitters are random.Recently, power allocation strategies for D2D communicationin random network models were studied and analyzed. The interference from underlay cognitivenodes was analyzed in based on several transmit powerallocation and receiver association schemes, the effect of the mode selection and power allocation of D2D communicationon cellular network performance was investigated. Tomaximize the D2D sum rate, on-off power allocation wasproposed and analyzed by characterizing the D2Dtransmission capacity and optimizing the on-off threshold ofD2D pairs. Similarly, based on the conditional success probabilityof a typical D2D pair, SIR-aware access control wasproposed to maximize the area spectral efficiency ofD2D pairs., a distributed random access protocol wasdesigned and analyzed to avoid packet collision of D2D pairs,which protects D2D receivers by creating exclusion regions.However, these works only designed deterministic or on-offpower allocation schemes. In addition, none of these worksconsider flow control for delay-sensitive D2D applications.
PROPOSED SYSTEM:
we focus on the design of distributed flowcontrol and power allocation strategies for delay-aware D2Dcommunication underlaying large wireless networks, whichalso take into account the interference created by the D2Dpairs. Our main contribution is summarized as follows:• In order to guarantee the coverage probability of CUEsin a distributed manner, we employ the tools of stochasticgeometry to derive the time-average individual interferencebudget of each D2D pair, which represents theallowable transmit power level of D2D transmitters.• Given the time-average individual D2D interference budget,we formulate a set of individual stochastic optimizationproblems for delay-aware D2D communicationunderlaying multiple cells, to maximize the time-averagethroughput utility of each D2D pair, subject to D2Dqueueing stability and the individual D2D interferencebudget.• We design a distributed interference-and-delay-aware(DIDA) flow control and power allocation strategy basedon Lyapunov optimization and D2D received interferenceestimation. Although the power allocation problemis non-convex, we propose a low-complexity solutionby utilizing some special mathematical structure of theobjective function. Also, the queue length bound andthroughput bound of D2D pairs using the DIDA strategyare analytically derived. In particular, we prove that theCUE coverage probability guarantee can be distributivelysatisfied regardless of whether the interference estimationby D2D receivers is exact.• Four interference estimation methods for D2D pairs aredesigned and compared. These interference estimationmethods facilitate simultaneous power allocation by D2Dpairs in each time slot and alleviate the CSI sharing overhead.Extensive simulation results suggest that adaptiveinterference estimation methods are preferred to improvethe D2D performance.• We compare the DIDA strategy with Fixed and On-Offstrategies by simulation. The Fixed strategy deterministicallyconsumes the individual interference budget in eachtime slot. The On-Off strategy is modified from withthe satisfaction of individual interference budget. Simulationresults indicate that the DIDA strategy with adaptiveinterference estimation obtains significant performancegain over these two strategies.
CONCLUSIONS
In this paper, we investigate distributed delay-aware designfor D2D communication underlaying multiple cells, to maximizethe time-average throughput utility of each D2D pairwhile guaranteeing the queueing stability of D2D communicationand the coverage probability requirement of interiorCUEs. We derive the individual interference budget for eachD2D pair to guarantee the coverage probability of interiorCUEs and then propose a distributed interference-and-delayawareflow control and power allocation strategy, along withfour interference estimation methods. We also analyticallyderive the queue-length bound and throughput bound of D2Dpairs under the DIDA strategy. The throughput performanceof the proposed DIDA strategy with adaptive interferenceestimation is demonstrated through simulation and shown toexceed that of two known alternatives.
REFERENCES
[1] K. Doppler, M. Rinne, C. Wijting, C. Ribeiro, and K. Hugl, “Device-to-device communication as an underlay to LTE-advanced networks,”IEEE Commun. Mag., vol. 47, no. 12, pp. 42–49, Dec. 2009.
[2] G. Fodor, E. Dahlman, G. Mildh, S. Parkvall, N. Reider, G. Miklos,and Z. Turanyi, “Design aspects of network assisted device-to-devicecommunications,” IEEE Commun. Mag., vol. 50, no. 3, pp. 170–177,Mar. 2012.
[3] L. Lei, Z. Zhong, C. Lin, and X. Shen, “Operator controlled deviceto-devicecommunications in LTE-advanced networks,” IEEE Wirel.Commun., vol. 19, no. 3, pp. 96–104, Jun. 2012.
[4] D. Feng, L. Lu, Y. Yuan-Wu, G. Li, S. Li, and G. Feng, “Deviceto-devicecommunications in cellular networks,” IEEE Commun. Mag.,vol. 52, no. 4, pp. 49–55, Apr. 2014.
[5] X. Lin, J. Andrews, A. Ghosh, and R. Ratasuk, “An overview of 3GPPdevice-to-device proximity services,” IEEE Commun. Mag., vol. 52,no. 4, pp. 40–48, Apr. 2014.
[6] A. Ramezani-Kebrya, M. , B. Liang, G. Boudreau, and S. H. Seyedmehdi,“Optimal power allocation in Device-to-Device communicationwith SIMO uplink beamforming,” in Proc. IEEE SPAWC, Stockholm,Sweden, June 2015, pp. 425–429.
[7] R. AliHemmati, B. Liang, M. , G. Boudreau, and S. H. Seyedmehdi,“Long-term power allocation for multi-channel device-to-devicecommunication based on limited feedback information,” in Proc. ASILOMAR,Pacific Grove, California, Nov. 2016, pp. 729–733.
[8] A. Ramezani-Kebrya, M. , B. Liang, G. Boudreau, and S. H.Seyedmehdi, “Robust power optimization for Device-to-Device communicationin a multi-cell network under partial CSI,” in Proc. IEEEICC, Paris, France, May 2017._2
[9] C.-H. Yu, K. Doppler, C. Ribeiro, and O. Tirkkonen, “Resource sharingoptimization for device-to-device communication underlaying cellularnetworks,” IEEE Trans. Wireless Commun., vol. 10, no. 8, pp. 2752–2763, Aug. 2011.
[10] P. Liu, C. Hu, T. Peng, R. Qian, and W. Wang, “Admission and powercontrol for device-to-device links with quality of service protectionin spectrum sharing hybrid network,” in Proc. IEEE PIMRC, Sydney,Australia, Sept. 2012, pp. 1192–1197.
[11] F. Teng, D. Guo, M. Honig, W. Xiao, and J. Liu, “Power control basedon interference pricing in hybrid D2D and cellular networks,” in Proc.IEEE Globecom Wkshps, Anaheim, USA, Dec. 2012, pp. 676–680.
[12] R. Yin, C. Zhong, G. Yu, Z. Zhang, K. K. Wong, and X. Chen, “Jointspectrum and power allocation for D2D communications underlayingcellular networks,” IEEE Trans. Veh. Technol., vol. 65, no. 4, pp. 2182–2195, Apr. 2016.