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The implementation of directional antennas on either access point or user equipment (UE) operating on mmWave frequencies is mostly essential in mmWave networks. Transmit antenna selection (TAS) is a low hardware and software complexity beamforming mechanism which is currently becoming popular for mmWave UEs due to the small size of antennas in mmWave frequencies. The solution to optimal TAS problem is generally simple for one-tier networks, however, this problem is of high complexity for multi-tier underlay networks, wherein the interference imposed from low-priority secondary users should be controlled in order not to violate quality-of-service requirements of high-priority primary users. There exist two very recent articles in the literature studying the optimal UE-side TAS joint with network resource allocation for multi-tier mmWave device-to-device networks. Such works consider finding the optimal active transmit antennas, channels and transmit powers of all users at each time-step in a proactive manner which is generally of high complexity. In this work, for the case where existing resources need not to be recalculated, we consider two low-complexity reactive TAS together with power and channel allocation schemes for the new users requesting to be registered into the network. We manage to obtain the optimal power for the UEs in a reactive distributed manner and then allocate the optimal TAS and channels through converting the problem into a maximum weighted one-to-one matching game. Numerical results reveal the good performance of our proposed schemes. [ABSTRACT FROM AUTHOR]

Transmit antenna selection (TAS) at base station has been widely studied and employed in many communication networks (such as those using massive multiple-input multiple-output (MIMO) systems). Thanks to the small size of microstrip antenna elements applicable to millimeter-wave (mmWave) frequencies, the implementation of TAS in small user equipments (UEs) employing switchable directional antennas is recently becoming popular. In this paper, we consider device-to-device (D2D) communications underlaying a cellular network wherein each D2D UE is equipped with switchable transmit antennas. By employing Generalized Bender’s Decomposition (GBD) algorithm, we obtained the solution to the problem of globally optimal transmit antenna selection and channel allocation to D2D UEs together with transmit powers of cellular and D2D UEs. Although we reformulated the non-convex primal subproblem of the proposed GBD-based method into convex form, we further managed to obtain the corresponding closed-form solution through analytical manipulations; this extensively increased (at least 60 times) the execution speed of the proposed method as shown in the simulation results. [ABSTRACT FROM AUTHOR]

Employing switchable directional antennas in the user equipment (UE) is becoming a popular method to replace conventional beamforming methods. This approach is mainly applicable to mmWave networks due to the small size of directional microstrip antenna elements on corresponding frequencies, and requires exploiting proper transmit antenna selection (TAS) schemes to obtain the optimal directivity of selected active antennas. TAS is rather complex in the heterogeneous cellular networks with underlaid D2D communication. For each D2D user, selecting transmit antennas with maximum radiation gain does not necessarily lead to the optimal throughput due to the potential interference that might be imposed on other high priority users, thus, finding the optimal transmit antennas of users is generally a challenging issue in networks with multi-antenna D2D users. In this work, based on Lagrangian relaxation method, we propose a novel and efficient transmit antenna selection and resource (channel and power) allocation (ASRA) for D2D mmWave networks. In order to validate the performance of our proposed algorithm, we devise another efficient low-complexity greedy-based ASRA as well. Numerical results verify the performance of our proposed Lagrangian-based ASRA in comparison to other methods. [ABSTRACT FROM AUTHOR]