# Device-To-Device Communication in 5G Environment: Issues, Solutions, and Challenges
## 5 Power Control
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Ref.** & **Problem** & **Proposed Method** & **Findings** & **Limitations** \\ \hline \multirow{3}{*}{[59]} & Power control distribution. & Theoretic framework using Mean Field Game (MFG). & Achieves higher energy efficiency compared with the blind power control scheme. & Increasing the energy means increasing the interference power and decreases the spectrum efficiency. \\ \hline \multirow{3}{*}{[60]} & Imperfect wireless Channel State Information (CSI) power control. & Truncated channel inversion and ON-OFF power control scheme. & Imperfect CSI and misinformation lead to the degradation of performance especially for high target SINR. & Estimation error is a key parameter that should be consider during network design. \\ \hline \multirow{3}{*}{[61]} & Contamination and training sequence overhead reduction in D2D under massive MIMO networks. & Revised Graph Coloring-based Pilot Allocation (RGCPA) algorithm. & Pilot overhead is reduced and the effect of pilot contamination is cancelled. & The sum power monotonically decreases and decreases and converges rapidly for different value. \\ \hline \multirow{3}{*}{[62]} & Sparse Code Multiple Access (SCMA) power allocation. & Graph theoretic approach. & Energy efficiency performance is enhanced and network capacity is upgraded. & Need to compare the algorithms with different schemes. \\ \hline \multirow{3}{*}{[63]} & Power control under different constraints. & Power control scheme using Particle Swarm Optimization (PSO). & Achieves higher throughput than the optimal strategy. & Combine the addition control into power control scheme and the joint channel allocation. \\ \hline \multirow{3}{*}{[64]} & Power control is non-convex and intractable. & D2D transmit power control schemes. & D2D rates converge to a rate ceiling at high signal-to-noise ratio. & The energy signal transmission is less effective when performance gaps are small. \\ \hline \multirow{3}{*}{[65]} & Non- convex mixed-integer fractional program. & Sequential Geometric Programming (SGP) algorithm. & Reduces energy efficiency (EE) loss. & The network EE first increases and then decreases when the transmit power increases. \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Summary of power control issues and proposed solutions. allocation (CA) scheme and a set of three power control (PC) schemes to manage the interference in D2D as a random network model based on stochastic geometry. According to the authors, it is possible to obtain a closed-form analytical expression for ergodic sum-rates and coverage probabilities, which shows the interactions of various network parameters that affect the link performance and the service quality. However, the proposed schemes are examined in single-cell scenarios only. The authors in [69; 70] use Peukert's Law (which shows the capacity of batteries changes at different discharging rates) to model the battery lifetime and to distinguish the nonlinear effects in batteries. Multiple D2D pairs are allowed to simultaneously share the same channel, which leads to the increase in channel utilization. From the test results, it shows that the D2D user equipment (UE) battery life is lower than the cellular UE if the distance of D2D UEs is more than 0.8 of the cell radius. When the UE is at a certain distance, it is advantageous to control the devices by communicating directly. [PERSON] et al. in [60] highlight that the main shortcoming in most of the papers in the literature is that the consideration of unrealistic assumptions. For example, most of the authors rely on deterministic values such as fixed transmission power, fixed distance between the receiver and D2D transmitter, and fixed SINR targets. Furthermore, they typically consider only just one cellular user that shares the resources with the D2D links. That is why in this paper, the authors present a centralized and distributed power control algorithm in a one-cell random-network model.