Wireless resource virtualization has garnered increasing attention in recent times. Some of the literature investigated this idea from different aspects. A survey of the works done on wireless virtualization as well as the models adopted and challenges encountered
was presented in [152]. Kamelet al. [153] proposed an efficient resource allocation scheme
of resource blocks in virtualized LTE networks. A mixed integer non-linear programming problem was formulated and was divided into two sub-problems due to its complexity. These sub-problems were solved iteratively and repeatedly until an optimal solution was
reached. Yang et al. [155] presented an opportunistic spectrum sharing scheme that
improves revenues, resource utility, and acceptance rate while simultaneously decreasing the cost for virtual networks.
D2D communication is another proposed solution for satisfying the increasing data demand which garnered attention in recent literature works. A comprehensive survey about D2D communication, its taxonomy, and the challenges it faces was presented in [147]. Resource allocation in D2D communication has been a particular area of interest [159, 160]. For example, a joint mode selection and resource allocation scheme that met the Quality-of-Service (QoS) requirements and suppressed the interference was developed in [159]. In [160], the optimal system resource allocation and mode selection for mobile content downloading was presented.
Some works in the literature have investigated power-efficient algorithms in LTE systems and can be categorized into two main categories: resource allocation-based [178, 179, 180, 181, 182, 183] and on/off switching-based schemes [184, 185, 186]. As the name suggests, resource allocation-based schemes try to allocate resources in such a
way so that the power is reduced. Han et al. suggested a Link Adaptive (LA) heuristic
scheme that determines the transmission parameters based on current channel condi- tions [179]. The scheme is divided into two main steps. In the first step, resources blocks (RBs) are allocated to each user until their rate requirement is satisfied. In the second step, un-allocated RBs are allocated to users that can achieve the most transmit power reduction. Thus, the bandwidth is sacrificed by assigning more RBs to users to allow
them to transmit using a lower modulation and coding scheme (MCS) to become more power-efficient. The downside of this scheme is that it assumes that the highest possible
MCS and then moving to a lower MCS by assigning more RBs. Shen et al. proposed
a power water-filling based scheme to determine the optimal power allocation for the different users [180]. The scheme allocates more power into channels with higher gains. Iterative methods such as Newton-Raphson were needed to solve a set of nonlinear equa- tions in order to determine the optimal solution with each iteration having a complexity
of O(K). However, two main shortcomings are observed. First, the scheme assumes
that a user can be allocated different power levels on different RBs allocated to it which is not allowed in LTE. Second, the problem might not be feasible because some users might have bad channel conditions and thus will not be allocated channels in the first place. Gao proposed a joint mode selection, channel allocation, and power allocation heuristic that first determines the communication mode (cellular/D2D) then determines the channel and power allocation. However, this algorithm doesn’t guarantee a minimum rate requirement and thus might violate the QoS requirements of users.
On the other hand, on/off switching-based schemes rely on switching devices be-
tween the on and off states in order to save energy. Chu et al. proposed a power saving
scheme that minimizes the “wake-up” time of the users based on the discontinuous re- ception (DRX) feature in LTE [184]. The problem was formulated as a nonlinear integer programming problem and solved heuristically by searching along the vertices of the polytope. However, the scheme does not take into consideration minimum rate require-
ments. Fowler et al. presented a comparison between using a fixed frame DRX cycle
and a dynamic DRX cycle in terms of power saving factor and wake-up delay. Results showed that there is a trade-off between these two parameters. However, this scheme also
doesn’t take into consideration a minimum rate requirement [185]. Mushtaq et al. also
took advantage of the DRX feature available in LTE. A scheduling scheme was proposed that satisfies key quality-of-service (QoS) parameters such as throughput, packet delay and packet losses while also saving power. Nonetheless, this work doesn’t quantify the power savings as it only stated that the longer the DRX sleep duration is, the more power is saved [186].
In this chapter, we:
to-device communication underlaying cellular network as a mixed integer non-linear programming problem (MINLP).
• Divide the problem into four smaller linear programming problems and solve them
to optimality.
• Develop two low-complexity heuristic algorithms, each to solve the power allocation
problem for cellular and D2D users respectively.
To the best of our knowledge, no previous work addresses power-aware wireless virtualized resource allocation and sharing with underlaying D2D communication.