Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Article Citation - WoS: 2Citation - Scopus: 2Deep Learning Based Adaptive Bit Allocation for Heterogeneous Interference Channels(Elsevier, 2021) Aycan, Esra; Özbek, Berna; Le Ruyet, DidierThis paper proposes an adaptive bit allocation scheme by using a fully connected (FC) deep neural network (DNN) considering imperfect channel state information (CSI) for heterogeneous networks. Achieving an accurate CSI has a crucial role on the system performance of the heterogeneous networks. Different quantization techniques have been employed to reduce the feedback overhead. However, the system performance cannot increase linearly with the number of bits increasing exponentially. Since optimizing the total number of bits is too complex for the entire network, an initial step is performed to distribute the bits to each cell in the conventional method. Then, the distributed bits are further allocated to each channel optimally. In order to enable direct allocation for the entire network, a FC-DNN based method is presented in this study. The optimized number of bits can be directly obtained for a different number of bits and scenarios by the proposed approach. The simulations are performed by using various scenarios with different allocation schemes. The performance results show that the DNN based method achieves a closer performance to the conventional approach. (C) 2021 Elsevier B.V. All rights reserved.Article Citation - Scopus: 1On Stream Selection for Interference Alignment With Limited Feedback in Heterogeneous Networks(John Wiley and Sons Inc., 2016) Aycan, Esra; Özbek, Berna; Le Ruyet, DidierThis paper presents a stream selection based interference alignment approach with imperfect channel state information for heterogeneous networks. The proposed solution constructs stream sequences by selecting only the strongest stream of each user where the first stream of the constructed stream sequences is associated to a pico user. While selecting the streams, the channel matrices of the unselected streams are projected orthogonally to the virtual transmit and receive channels of the selected stream in order to align the interference in the null space of these virtual channels. In addition, the influence of imperfect channel state information on the proposed algorithm is analysed. A bit allocation scheme is given by deriving an upper bound on the rate loss because of quantisation. The simulation results are carried out by considering various scenarios with different locations of pico cells at the cell edge regions of the macro cell. The performance results show that the proposed algorithm with the imperfect channel state information achieves higher performance than the existing algorithms.Article Citation - WoS: 6Citation - Scopus: 9Adaptive Limited Feedback Links for Cooperative Multi-Antenna Multicell Networks(Springer Verlag, 2014) Özbek, Berna; Ruyet, Didier LeThe overall performance of cooperative networks is quite sensitive to channel state information (CSI) of serving and interfering base stations (BSs) and affected strongly by quality of limited feedback links. In this paper, we propose two adaptive limited feedback strategies for intercell interference cancelation in multi-antenna multicell networks. The first proposed strategy is developed to improve average multicell capacity assuming a fixed rate feedback link. This algorithm is based on adaptation of the number of bits to quantize CSI of serving and interfering BSs according to transmitter power and location of the user in its own cell. The second proposed strategy is designed in a way to increase average capacity of cell-edge users assuming an adaptive rate feedback link. This algorithm is based on the idea of allocating more bits to quantize CSI of users at cell-edge regions while allocating less bits for users near the serving BS. We illustrate performance of the proposed feedback links for downlink cooperative multi-antenna multicell networks in wireless channels.
