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In this paper, in order to reduce the energy consumption and time of data transmission, the non-orthogonal multiple access (NOMA) and mobile edge caching technologies are jointly considered in mobile edge computing (MEC) networks. As for the cache-assisted vehicular NOMA–MEC networks, a problem of minimizing the energy consumed by vehicles (mobile devices, MDs) is formulated under time and resource constraints, which jointly optimize the computing resource allocation, subchannel selection, device association, offloading and caching decisions. To solve the formulated problem, we develop an effective joint computation offloading and task-caching algorithm based on the twin-delayed deep deterministic policy gradient (TD3) algorithm. Such a TD3-based offloading (TD3O) algorithm includes a designed action transformation (AT) algorithm used for transforming continuous action space into a discrete one. In addition, to solve the formulated problem in a non-iterative manner, an effective heuristic algorithm (HA) is also designed. As for the designed algorithms, we provide some detailed analyses of computation complexity and convergence, and give some meaningful insights through simulation. Simulation results show that the TD3O algorithm could achieve lower local energy consumption than several benchmark algorithms, and HA could achieve lower consumption than the completely offloading algorithm and local execution algorithm. [ABSTRACT FROM AUTHOR]

The beam direction constrained problem is one of the important issues to be solved in millimeter-wave (mmWave) wideband communications when serving multi-user with squint beams whose direction varies with frequency. In this paper, we improve the number of simultaneous users served by collaboratively transmitting squint beams among multi-subarray at the base station (BS) end in a downlink multi-user line-of-sight (LoS) scenario, and reduce the interference among co-channel squint beams by a beam domain approach. The optimization problem of maximizing the number of users served in the system by transmitting beams in the two-dimensional beamspace of the planar antenna subarray is proposed and its suboptimal algorithm is given. Finally, the feasibility of the proposed method and the performance of the proposed algorithm are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

In heterogeneous cellular networks (HCNs), the energy reduction has a great impact on the operational cost and global carbon footprint, which has attracted more and more attention. To enhance the network energy efficiency (EE), we design two types of association mechanisms integrated with open loop power control (OLPC) for uplink code-division-multiple-access (CDMA) enabled HCNs. Specifically, they are formulated into two optimization problems that maximize the sum of users' EEs and the one of users' EE utilities. It is noteworthy that the one of these two mechanisms guarantees the user fairness by employing a logarithmic function. Considering that these formulated problems are in a fractional mixed-integer form and hard to tackle, we utilize a coalitional game to design two types of association algorithms with guaranteed convergence. To show the effectiveness of designed algorithms, another one is introduced for comparison in the simulation. As for them, we mainly investigate the impacts of user and BS densities on the association performance. [ABSTRACT FROM AUTHOR]

Proposed by Maddah-Ali and Niesen, a coded caching scheme has been verified to alleviate the load of networks efficiently. Recently, a new technique called placement delivery array (PDA) was proposed to characterize the coded caching scheme. In this paper, we consider a caching system in the scope of ultra dense networks (UDNs). Each base station (BS) has a finite cache and stores some contents. We propose an efficient coded content caching scheme called double coded caching to make the transmission robust to in-and-out wireless network quality. Then the dynamic caching and multicast scheduling are considered to jointly minimize the average delay and power of the content-centric wireless networks. This stochastic optimization problem can be formulated as a Markov decision process (MDP) with unknown transition probabilities and large state space. We propose a deep reinforcement learning approach to deal with the decision problem. Our algorithm uses a variational auto-encoder (VAE) neural network to approximate the state sufficiently, and uses a weighted double Q-learning scheme to reduce variance and overestimation of the Q function. Numerical results demonstrate that the proposed double coded caching scheme increases the probability of the successful transmission, and the caching and scheduling policy can effectively reduce the delay and the power consumption. [ABSTRACT FROM AUTHOR]

In heterogeneous cellular networks (HCNs), the deployed small cell base stations share the same spectrum resource with that of macro base station, which causes cross-tier interferences and the performance depreciation of the system. This paper investigates the downlink outage performance of HCNs and its resource allocation problem to mitigate interferences. Specifically, we first derive closed-form expressions of overall outage probability of the system. Then, the resource allocation problem is proposed to reduce the outage probability of HCNs. This problem is formulated as a matching game, and a stable matching is considered to be the solution. Finally, to address this matching problem, a distributed algorithm is proposed which can find a stable matching. Both analytical results and simulations show that the proposed algorithm improves the overall performance of HCNs. [ABSTRACT FROM AUTHOR]

In this paper, we present two novel interference management stratagems for coexisting one primary user (PU) and multiple secondary users (SUs) by exploiting the unused spatial directions at PU. The cognitive stations sense their environment to determine the users they are interfering with, and adapt to it by designing the corresponding precoders using interference alignment (IA) in order to avoid causing performance degradation to nearby PU and SUs. The first proposed approach judiciously designs the set of precoders based on an improved version of minimum weighted leakage interference algorithm. However, there are still leftover interference signals in SUs’ desired signal space due to the limited iterative times in the first algorithm. To tackle this problem, another scheme combining the first one and power allocation method at the secondary stations is developed. Numerical results validate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In this paper, the joint transceiver design issue is investigated for multi-cell systems with multiple mobile terminals (MTs). An optimization problem is formulated based on the criterion of mean squared error minimization for the joint design of the cooperative precoder of all multi-input multi-output (MIMO) cells and the cooperative decoder of all MIMO MTs. With a fixed decoder, the optimum precoder is first derived in a closed-form expression, where no exchange of data streams among all of the MIMO cells is required due to the limited capability of the backhaul. Subsequently, an optimum decoder is then obtained in an analytical expression with the fixed precoder. Based on these two expressions, an iterative algorithm with guaranteed convergence is finally developed to carry out the joint optimization of the cooperative precoders and decoders. Simulation results demonstrating the effectiveness of the proposed algorithm are also provided. [ABSTRACT FROM AUTHOR]