Efficient feedback scheme based on compressed sensing in MIMO wireless networks

Lu, Wei; Liu, Yingzhuang; Wang, Desheng

doi:10.1016/j.compeleceng.2012.02.006

Cited by 11 publications

(6 citation statements)

References 21 publications

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“…The authors did not investigate the effect of estimation and its MIMO technique has not been examined in this work. A CQI feedback overhead reduction scheme based on compressive sensing (CS) theory was proposed in [26,27]. In this scheme, the eNodeB uses CS to identify strong users whose SNRs are larger than the threshold based on channel quality at a certain correlation in time and frequency.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

Abdulhasan

Salman

et al. 2015

Wireless Pers Commun

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Channel quality indicator (CQI) feedback in long-term evolution (LTE) system is an essential technique in describing the instantaneous channel state information. The CQI calculations highly depend on the accuracy of the channel estimation process in order to assign appropriate modulation and coding scheme. However, one of the critical issues affecting the LTE system performance is obtaining the CQI for each transmission period which will inevitably cost many resources. Therefore, an appropriate method for reducing CQI feedback overhead along with accurate channel estimation technique is required to manage the allocated resources and obtains significant improvements in system performance. In this paper, an adaptive threshold feedback compression scheme based on CQI scheme is proposed to obtain better system performance in terms of system throughput and error rate in LTE system. This proposed adaptive scheme dynamically adapts its threshold level to the signal to noise ratio variations, thus increasing the throughput and reducing the CQI feedback overhead. Results show that the proposed CQI based adaptive threshold feedback compression scheme enhances the tradeoff between system throughput and block error rate.

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Section: Related Workmentioning

confidence: 99%

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

Abdulhasan

Salman

et al. 2015

Wireless Pers Commun

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“…As stated in (19) and (22), the LS and BLUE estimators are noisy which means that the estimated SNR can be higher or lower than the actual one. This is problematic, since an estimated SNR higher than the actual one results in a transmission rate higher than the maximum rate the end user can support.…”

Section: E Snr Back-offmentioning

confidence: 99%

“…this, we back-off on the estimated noisy SNRs. From (19) and (22), each entry ofx S andv I respectively can be represented in a scalar equation asγ = γ + e, where γ andγ stands for the actual and the estimated SNRs respectively, and e is the Gaussian error. Our back-off strategy simply subtracts an amount ∆ from γ. Hence,…”

Section: E Snr Back-offmentioning

confidence: 99%

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On the Feedback Reduction of Multiuser Relay Networks Using Compressive Sensing

Elkhalil

Eltayeb

Kammoun

et al. 2016

IEEE Trans. Commun.

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In this paper, we propose a feedback reduction scheme for full-duplex relay-aided multiuser networks. The proposed scheme permits the base station (BS) to obtain channel state information (CSI) from a subset of strong users under substantially reduced feedback overhead. More specifically, we cast the problem of user identification and CSI estimation as a block sparse signal recovery problem in compressive sensing (CS). Using existing CS block recovery algorithms, we first obtain the identity of the strong users and then estimate their CSI using the best linear unbiased estimator (BLUE). To minimize the effect of noise on the estimated CSI, we introduce a back-off strategy that optimally backsoff on the noisy estimated CSI and derive the error covariance matrix of the post-detection noise. In addition to this, we provide exact closed form expressions for the average maximum equivalent SNR at the destination user. Numerical results show that the proposed algorithm drastically reduces the feedback air-time and achieves a rate close to that obtained by scheduling schemes that require dedicated error-free feedback from all the network users.

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“…The theoretical analysis and simulations show that the energy consumption decreases by 81 and 36 % compared to existing solutions. Wei Lu et al [19] propose a compressed sensing feedback scheme for zero-forcing beam-forming in order to enhance the throughput in MIMO broadcast channel. Simulation-based results show that the proposed scheme has good performances compared to existing feedback schemes.…”

Section: Related Workmentioning

confidence: 99%

Achieving QoS in Virtual MIMO systems: a satisfaction equilibrium analysis

Bennani

Sabir

Kobbane

et al. 2016

J Wireless Com Network

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This paper presents a game theoretic framework to analyze a cellular-WLAN heterogeneous network from a virtual multiple-input multiple-output (VMIMO) perspective. Namely, we restrict to the uplink case and consider a non-cooperative game where each user seeks to meet some quality of service (QoS). Moreover, mobile users are allowed to re-inject, through their WLAN interfaces, a part of their throughput in the induced game. Thus, the interaction among users defines a distributed VMIMO with a possibly throughput exchange. This mechanism will help all users to meet their respective QoS expressed by the perceived average throughput. The average throughput is considered to be the utility function used in this framework. Now, each mobile user experiences a certain throughput composed of two parts: (1) the throughput received from cellular subsystem and (2) the throughput received from WLAN subsystem. Naturally, we use the concept of satisfaction equilibrium to predict the behavior of the network. Indeed, we provided a sufficient condition for the existence of such an equilibrium. Next, we prove the uniqueness of the equilibrium and compute it explicitly. Afterward, we propose a fully distributed algorithm inspired from the well-known Banach-Picard learning algorithm. Our scheme has many good features facilitating its implementation and usability. Indeed, it accurately converges to the equilibrium (if exists), it is very fast, and it requires no external information. Simulation results validate the algorithm and show its robustness and illustrate numerically the proposed learning scheme for quality-of-service management in such a heterogeneous network.

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Efficient feedback scheme based on compressed sensing in MIMO wireless networks

Cited by 11 publications

References 21 publications

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

An Adaptive Threshold Feedback Compression Scheme Based on Channel Quality Indicator (CQI) in Long Term Evolution (LTE) System

On the Feedback Reduction of Multiuser Relay Networks Using Compressive Sensing

Achieving QoS in Virtual MIMO systems: a satisfaction equilibrium analysis

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