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In this paper, we design a new smart software-defined radio access network architecture which is flexible and traffic and density aware for the fifth generation (5G) of cellular wireless networks and beyond. The proposed architecture, based on network parameters such as density of users and system traffic, performs five important tasks namely, dynamic radio resource management (RRM), dynamic BS type selection, dynamic functionality splitting, dynamic transmission technology selection, and dynamic framing. In this regard, we first elaborate the structure of the proposed smart soft-RAN model and explain the details of the proposed architecture and RRM algorithms. Next, as a case study, based on the proposed architecture, we design a novel coordinated multi point beamforming technique to enhance the throughput of a virtualized software defined-based 5G network utilizing the combination of power domain non-orthogonal multiple access and multiple-input single-output downlink communication. In doing so, we formulate an optimization problem with the aim of maximizing the total throughput subject to minimum required data rate of each user and maximum transmit power constraint of each mobile virtual network operator and each BS, and find jointly the non-orthogonal set, beamforming, and subcarrier allocation. To solve the proposed optimization problem, based on the network density, we design two centralized and semi-centralized algorithms. Specifically, for the ultra-dense scenario, we use the centralized algorithm while the semi-centralized one is used for the high and moderate density scenarios. Numerical results illustrate the performance and signaling overhead of the proposed algorithms, e.g., taking computational limitations into account the number of supported users is increased by more than 60%., Comment: There is one fundamental issue in the interference cancellation protocol of the CoMP-NOMA system. The latter CoMP-NOMA model is revised in the following work: arXiv:2007.10013v3

Software-defined networking (SDN) as a new paradigm for networking provides efficient resource reallocation platform in emerging cloud data center networks. The dynamic nature of cloud data center network's traffic, as well as the existence of big flows make it necessary to periodically reprogram the network through the SDN controller. Therefore, it is critical for network researchers to minimize the side-effects of network reconfiguration. In this way, the most challenging issue is the number of rerouted flows that affect the network stability and QoS parameters. As a result, dynamic reconfiguration of the network with minimum overhead (i.e. minimum flow rerouting) is an interesting problem in SDN-based resource reallocation. In this paper, we mathematically formulated the resource reallocation problem as an optimization problem with minimum network reconfiguration overhead subject to QoS requirements of the applications flows. In order to reduce the time complexity of solving the optimization problem, a forwarding table compression technique is devised making the proposed scheme an efficient resource reallocation method which can be used as an application on top of the SDN controller. Our Experimental results show that the proposed scheme decreases the network reconfiguration overhead dramatically while meeting the QoS constraints. Since the reconfiguration overhead of the proposed scheme is low, the controller can reallocate the resources more frequently based on the network condition. We also studied the impact of the proposed network reconfiguration scheme on packet loss and delay in the network. The results show that the proposed approach outperform the conventional methods.

The highly dynamic nature of the current network traffics, makes the network managers to exploit the flexibility of the state-of-the-art paradigm called SDN. In this way, there has been an increasing interest in hybrid networks of SDN-MPLS. In this paper, a new traffic engineering architecture for SDN-MPLS network is proposed. To this end, OpenFlow-enabled switches are applied over the edge of the network to improve flow-level management flexibility while MPLS routers are considered as the core of the network to make the scheme applicable for existing MPLS networks. The proposed scheme re-assigns flows to the Label-Switched Paths (LSPs) to highly utilize the network resources. In the cases that the flow-level re-routing is insufficient, the proposed scheme recomputes and re-creates the undergoing LSPs. To this end, we mathematically formulate two optimization problems: i) flow re-routing, and, ii) LSP re-creation and propose a heuristic algorithm to improve the performance of the scheme. Our experimental results show the efficiency of the proposed hybrid SDN-MPLS architecture in traffic engineering superiors traditionally deployed MPLS networks.

In this paper, we propose a cross layer energy efficient resource allocation and remote radio head (RRH) selection algorithm for heterogeneous traffic in power domain - non-orthogonal multiple access (PD-NOMA) based heterogeneous cloud radio access networks (H-CRANs). The main aim is to maximize the EE of the elastic users subject to the average delay constraint of the streaming users and the constraints, RRH selection, subcarrier, transmit power and successive interference cancellation. The considered optimization problem is non-convex, NP-hard and intractable. To solve this problem, we transform the fractional objective function into a subtractive form. Then, we utilize successive convex approximation approach. Moreover, in order to increase the processing speed, we introduce a framework for accelerating the successive convex approximation for low complexity with the Lagrangian method on graphics processing unit. Furthermore, in order to show the optimality gap of the proposed successive convex approximation approach, we solve the proposed optimization problem by applying an optimal method based on the monotonic optimization. Studying different scenarios show that by using both PD-NOMA technique and H-CRAN, the system energy efficiency is improved.

Information-theoretic secrecy, in particular the wiretap channel formulation, provides protection against interception of a message by adversary Eve and has been widely studied in the last two decades. In contrast, covert communications under an analogous formulation provides protection against even the detection of the presence of the message by an adversary, and it has drawn significant interest recently. These two security topics are generally applicable in different scenarios; however, here we explore what can be learned by studying them under a common framework. Under a similar but not identical mathematical formulation, we introduce power optimization problems for each of the secrecy and the covert communications scenario, and we exploit common aspects of the problems to employ similar tools in their respective optimizations. Moreover, due to the practical limitations, we assume only channel, Comment: 20 pages, 6 figures, two tables

The proliferation of cloud data center applications and network function virtualization (NFV) boosts dynamic and QoS dependent traffic into the data centers network. Currently, lots of network routing protocols are requirement agnostic, while other QoS-aware protocols are computationally complex and inefficient for small flows. In this paper, a computationally efficient congestion avoidance scheme, called CECT, for software-defined cloud data centers is proposed. The proposed algorithm, CECT, not only minimizes network congestion but also reallocates the resources based on the flow requirements. To this end, we use a routing architecture to reconfigure the network resources triggered by two events: 1) the elapsing of a predefined time interval, or, 2) the occurrence of congestion. Moreover, a forwarding table entries compression technique is used to reduce the computational complexity of CECT. In this way, we mathematically formulate an optimization problem and define a genetic algorithm to solve the proposed optimization problem. We test the proposed algorithm on real-world network traffic. Our results show that CECT is computationally fast and the solution is feasible in all cases. In order to evaluate our algorithm in term of throughput, CECT is compared with ECMP (where the shortest path algorithm is used as the cost function). Simulation results confirm that the throughput obtained by running CECT is improved up to 3x compared to ECMP while packet loss is decreased up to 2x.

This paper addresses the four enabling technologies, namely multi-user sparse code multiple access (SCMA), content caching, energy harvesting, and physical layer security for proposing an energy and spectral efficient resource allocation algorithm for the access and backhaul links in heterogeneous cellular networks. Although each of the above mentioned issues could be a topic of research, in a real situation, we would face a complicated scenario where they should be considered jointly, and hence, our target is to consider these technologies jointly in a unified framework. Moreover, we propose two novel content delivery scenarios: 1) single frame content delivery (SFCD), and 2) multiple frames content delivery (MFCD), where the time duration of serving user requests is divided into several frames. In the first scenario, the requested content by each user is served over one frame. However, in the second scenario, the requested content by each user can be delivered over several frames. We formulate the resource allocation for the proposed scenarios as optimization problems where our main aim is to maximize the energy efficiency of access links subject to the transmit power and rate constraints of access and backhaul links, caching and energy harvesting constraints, and SCMA codebook allocation limitations. Due to the practical limitations, we assume that the channel state information values between eavesdroppers and base stations are uncertain and design the network for the worst case scenario. Since the corresponding optimization problems are mixed integer non-linear and nonconvex programming, NP-hard, and intractable, we propose an iterative algorithm based on the well-known alternate and successive convex approximation methods.

Recently, wireless edge caching has been emerged as a promising technology for future wireless networks to cope with exponentially increasing demands for high data rate and low latency multimedia services by proactively storing contents at the network edge. Here, we aim to design efficient cache placement and delivery strategies for an orthogonal frequency division multiple access (OFDMA)-based cache-enabled heterogeneous cellular network (C-HetNet) which operates in two separated phases: caching phase (CP) and delivery phase (DP). Since guaranteeing fairness among mobile users (MUs) is not well investigated in cache-assisted wireless networks, we first propose two delay-based fairness schemes called proportional fairness (PF) and min-max fairness (MMF). The PF scheme deals with minimizing the total weighted latency of MUs while MMF aims at minimizing the maximum latency among them. In the CP, we propose a novel proactive fairness and transmission-aware cache placement strategy (CPS) corresponding to each target fairness scheme by exploiting the flexible wireless access and backhaul transmission opportunities. Specifically, we jointly perform the allocation of physical resources as storage and radio, and user association to improve the flexibility of the CPSs. Moreover, In the DP of each fairness scheme, an efficient delivery policy is proposed based on the arrival requests of MUs, CSI, and caching status. Numerical assessments demonstrate that our proposed CPSs outperform the total latency of MUs up to 27% compared to the conventional baseline popular CPSs., Comment: 42 pages, 13 figures, under review in IEEE Transactions on Mobile Computing (TMC)

In this paper, a novel method for joint radio resource allocation (RRA), three-dimensional placement (3DP), and user association of aerial base stations (ABSs) as a main problem in the internet of things (IoT) networks is proposed. In our proposed model, we consider two schemes: a) line of sight (LoS) b) generalized. In the LoS scheme, all the ABSs should see the IoT users as LoS. In the generalized scheme, ABSs can see some of the IoT users as LoS and some of them as NLoS. The main goal of this paper is to minimize the overal transmit power of the IoT users while satisfying some quality of service (QoS) constraints in uplink scenario. To solve the optimization problems and to convert the main problems with high complexity into the subproblems with lower complexity, we decompose them into two subproblems namely 3DP subproblem and joint RRA and user association (JRU) subproblem. The methods which we use to solve our proposed optimization problems are Semi Definite Relaxation (SDR) and Geometric Programming (GP). Finally, using simulations, we evaluate the performance of the proposed schemes for different values of the network parameters., Comment: 10 pages, 6 figures, 3 tables, submitted to journal

In this paper, we propose a device to device (D2D) communication scenario underlaying a cellular network where both D2D and cellular users (CUs) are discrete power-rate systems with limited feedback from the receivers. It is assumed that there exists an adversary which wants to eavesdrop on the information transmission from the base station (BS) to CUs. Since D2D communication shares the same spectrum with cellular network, cross interference must be considered. However, when secrecy capacity is considered, the interference caused by D2D communication can help to improve the secrecy communications by confusing the eavesdroppers. Since both systems share the same spectrum, cross interference must be considered. We formulate the proposed resource allocation into an optimization problem whose objective is to maximize the average transmission rate of D2D pair in the presence of the cellular communications under average transmission power constraint. For the cellular network, we require a minimum average achievable secrecy rate in the absence of D2D communication as well as a maximum secrecy outage probability in the presence of D2D communication which should be satisfied. Due to high complexity convex optimization methods, to solve the proposed optimization problem, we apply Particle Swarm Optimization (PSO) which is an evolutionary approach. Moreover, we model and study the error in the feedback channel and the imperfectness of channel distribution information (CDI) using parametric and nonparametric methods. Finally, the impact of different system parameters on the performance of the proposed scheme is investigated through simulations. The performance of the proposed scheme is evaluated using numerical results for different scenarios., Comment: IEEE Transactions on Vehicular Technology, 2017

In this paper, a new approach for multiple access (MA) in fifth generation (5G) of cellular networks called power domain sparse code multiple access (PSMA) is proposed. In PSMA, we adopt both the power domain and the code domain to transmit multiple users' signals over a subcarrier simultaneously. In such a model, the same SCMA codebook can be used by multiple users where, for these users, power domain non-orthogonal multiple access (PD-NOMA) technique is used to send signals non-orthogonally. Although different SCMA codebooks are orthogonal and produce no interference over each other, the same codebook used by multiple users produces interference over these users. We investigate the signal model as well as the receiver and transmitter of the PSMA method. To evaluate the performance of PSMA, we consider a heterogeneous cellular network (HetNet). In this case our design objective is to maximize the system sum rate of the network subject to some system level and QoS constraints such as transmit power constraints. We formulate the proposed resource allocation problem as an optimization problem and solve it by successive convex approximation (SCA) techniques. Moreover, we compare PSMA with sparse code multiple access (SCMA) and PD-NOMA from the performance and computational complexity perspective. Finally, the effectiveness of the proposed approach is investigated using numerical results. We show that by a reasonable increase in complexity, PSMA can improve the spectral efficiency about 50\% compared to SCMA and PD-NOMA., Comment: 11 pages, 8 figures, journal

This paper considers joint uplink/downlink of an orthogonal frequency division multiple access (OFDMA)-based heterogeneous network (HetNet) consisting of a single macro base station (MBS), multiple femto base stations (FBSs) and access points (APs) where base stations (BSs) can offload data to APs and each mobile user (MU) is able to harvest the received energy using the simultaneous wireless information and power transfer (SWIPT) technique. We also suppose that the harvested energy of MUs are used for their uplink information transmission. We devise a radio resource allocation (RRA) algorithm to maximize the uplink sum data rate of MUs subject to a minimum required downlink data rate of each MU and maximum allowable transmit power of each BS, AP, and MU. More specifically, both the frequency division duplex (FDD) and time division duplex (TDD) schemes are investigated. The proposed non-convex optimization problems are solved using an iterative algorithm. It is also proved that the proposed algorithm converges to a near-optimal solution. Simulation results illustrate that the TDD scheme improves the performance compared to the FDD scheme. In addition, it is shown that utilizing the data offloading technique improves the uplink sum data rate of MUs compared to the scenario without any AP., Comment: Due to the existence of a fundamental issue in the paper, we decided to withdraw it. The main issue of the paper, as the reviewers mentioned, is controlling both the cellular and WiFi complementary networks as a centralized manner. Moreover, the channel side information requirement grows tremendously because of this centralized approach

In this paper, the performance and system complexity of the candidate multiple access (MA) techniques for the next generation of cellular systems, namely, non-orthogonal multiple access (NOMA) (in this paper, we consider power domain MA as NOMA) and sparse code multiple access (SCMA), are investigated. To this end, for each MA technique, a resource allocation problem considering heterogeneous cellular networks (HetNet) is formulated. We apply successive convex approximation (SCA) method to each problem and obtain their solutions. The simulation results show that SCMA-based system achieves better performance than NOMA-based one at the cost of more complexity., Comment: 5 pages, 2 figures

The unprecedented growth of internet contents, specially social media, invoking a challenge to the load of cellular networks. In addition, nowadays, the demands of quality of experience (QoE) became a more practical norm in contrast of quality of service (QoS), in which downloading delay is an important factor of it. To satisfy this demand, we propose two resource allocation (RA) algorithms to optimize the place of social media in the cache of the Base stations (BSs) and radio resources (i.e., transmit powers and subcarriers), jointly in a multi-cell Orthogonal Frequency Division Multiple Access (OFDMA) based system. In the first scheme, the total downloading delay of the network is minimized, while in the second scheme, a fairness-aware scheme is proposed in which the maximum downloading delays is minimized. We propose iterative algorithms to solve each problem, where the content placement problem and the joint subcarrier and transmit power allocation problem will be iteratively optimized. We also prove that the proposed approaches converges to a near-optimal solution, as well as the number of iterations increases., Comment: We found a problem in the time scale of two separated phases known as caching and delivery phases