Resource Allocation in Millimeter-Wave Device-to-Device Networks

Table 1

Summary of mmwave D2D communication resource allocation solutions.

Reference	Target/objective	Method	Performance metric
[28]	Maximize energy efficiency and reduce transmission power in a full duplex (FD) relay-aided mmwave D2D communication	Lagrange dual decomposition and Karush–Kuhn–Tucker (KKT) conditions; Matching theory for relaying	Energy efficiency(EE); Transmit power; Jains’ fairness index
[29]	Maximize sum rate in a single-cell mmwave time division duplex cellular network by considering joint adaptive selection for multibeam reflection of NLOS devices and D2D relays	Lagrangian dual-based algorithm	Sum rate; Jains’ fairness index
[30]	Maximization of throughput in an outdoor mmwave small cell environment with a trade-off between number of admitted devices and interference constraint.	Heuristic algorithm	Throughput; Satisfaction ratio
[31]	Joint relay selection and power allocation to maximize system throughput and minimize aggregate transmission power by taking data rate threshold and total transmit power constraints	Matching theory	Transmit power; Throughput
[32]	Optimal subchannel allocation for underlay to maximize sum rate and spectrum efficiency for D2D communication in outdoor mmwave scenario	Iterative water filling algorithm	Sum rate; Spectrum efficiency; Jains’ fairness index
[33]	Optimal subchannel allocation for access and D2D links in a densely deployed multiple mmwave small cells to maximize sum rate	Coalition game	Sum rate
[34]	Enhance system throughput and spectrum efficiency in an urban scenario in the E-band by reducing interference from multiple D2D pairs	Heuristic algorithm	Throughput; D2D efficiency ratio
[35]	Maximize the network sum rate in D2D-enabled communication in heterogeneous cellular networks by combining mmwave and sub-6 GHz	Coalition formation game	Network sum rate
[36]	Maximize EE of the CUs served by either macrocells or mmwave small cells by considering simultaneous subcarrier and power allocation to satisfying a given QoS level for D2D pairs. The macrocells operate at 2.4 GHz and small cells operate at 28 GHz.	Lagrangian and Hungarian method	Energy efficiency; Outage probability of D2D pairs
[37]	Energy efficiency maximization for cellular and D2D user devices. The cellular devices are either served by macrocells or mmwave small cells and the QoS requirements of D2D users are maintained.	Lagrange technique and KKT conditions; Hungarian method	Energy efficiency; Sum rate; Outage probability
[38]	A Stackelberg game-based time-sharing technique proposed for interfering D2D communication paths to maximize throughput at 60 GHz	Stackelberg game	Throughput; D2D user density
[39]	Transmit power minimization scheme by considering device association and beamwidth selection in a 60 GHz mmwave D2D network	Particle swarm optimization (PSO)	Transmit power; Achievable rate
[40]	Resource allocation, beam selection, and interference coordination in integrated mmwave and sub-6 GHz network scenario with two-hop D2D relaying.	Graph theory	Throughput
[41]	Resource sharing in D2D communication for a mmwave and 4G system architecture with TDMA-based MAC structure	Nonlinear integer programming; Heuristic resource sharing scheme	Network capacity
[42]	Maximization of mmwave D2D throughput by joint allocation of transmit angle and time slot	Graph theory	Throughput
[43]	Minimize D2D link transmit power and maximize the achievable throughput	Stackelberg game	Transmit power; Throughput
[44]	Optimize outage probability for uplink cellular and D2D communicating users for a D2D-enabled mmwave network with clustered D2D pairs	Stochastic geometry and Laplace transform	Outage probability