This study proposes an incentive-based femtocell cooperation scheme for indoor macrocell users (MUs) in an underlay two-tier heterogeneous network which helps the indoor MUs to achieve higher data rate through time sharing access from the femtocell. Due to underlay spectrum sharing nature of the femtocell, the network suffers from severe cross-tier interference. To manage this cross-tier interference, a price-based power control scheme is also proposed for the femtocell access point (FAP) whereby the macrocell base station (MBS) controls the transmit power of the FAP by pricing their resulted cross-tier interference power level subject to a maximum tolerable interference limit. A Stackelberg game has been formulated and analysed for joint pricing-based power control and incentive-based cooperation game. Numerical results show the performance of the proposed scheme in terms of achievable rate of indoor users and utilities of both the MBS and the FAP for different locations of the femtocells.
We consider network coding for a noiseless broadcast channel where each receiver demands a subset of messages available at the transmitter and is equipped with noisy side information in the form an erroneous version of the message symbols it demands. We view the message symbols as elements from a finite field and assume that the number of symbol errors in the noisy side information is upper bounded by a known constant. This communication problem, which we refer to as broadcasting with noisy side information (BNSI), has applications in the re-transmission phase of downlink networks. We derive a necessary and sufficient condition for a linear coding scheme to satisfy the demands of all the receivers in a given BNSI network, and show that syndrome decoding can be used at the receivers to decode the demanded messages from the received codeword and the available noisy side information. We represent BNSI problems as bipartite graphs, and using this representation, classify the family of problems where linear coding provides bandwidth savings compared to uncoded transmission. We provide a simple algorithm to determine if a given BNSI network belongs to this family of problems, i.e., to identify if linear coding provides an advantage over uncoded transmission for the given BNSI problem. We provide lower bounds and upper bounds on the optimal codelength and constructions of linear coding schemes based on linear error correcting codes. For any given BNSI problem, we construct an equivalent index coding problem. A linear code is a valid scheme for a BNSI problem if and only if it is valid for the constructed index coding problem.
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