A novel resource allocation algorithm based on downlink and uplink decouple access scheme in heterogeneous networks

In order to reduce the energy consumption, we propose a novel Macro Base Station (MBS) sleep scheme based on the density of Pico Base Station (PBS) including three sleep approaches for current heterogeneous networks (het-net). Our scheme consists of two parts. In the first part, by setting thresholds for PBS density according to the total coverage of PBSs in a macro-coverage, we divide the network into three scenarios where PBSs are deployed densely, sparsely, and commonly correspondingly. In the second part, the MBS chooses one sleep approach of our scheme by comparing its PBS density with the thresholds. In each approach, minimizing the system energy consumption and meeting the QoS requirements are both considered as our goals. Particularly, the offset value is designed to guarantee blocking probability, especially when the neighboring MBSs are in charge of taking over the migrated users from the sleep MBS. Finally, simulation results demonstrate that the proposed scheme is much more efficient than the other existing schemes in terms of the power consumption and the blocking probability.

In this paper, the carrier aggregation (CA) is applied to Heterogeneous Networks (HetNets) consisting of a macro base station (MBS) and low-power pico base stations (PBSs). The PBSs are distributed in the outer space of the disk centered at the MBS and the closed-form solution of the radius of the disk is analyzed. In the CA based HetNet, firstly, a practical user association scheme is proposed to classify the users into macrocell user (MUs) and pico-cell users (PUs). Secondly, a PU-centric cooperative transmission strategy is proposed to increase the data rate of PUs. Then, in order to eliminate the cross-tier interference in HetNet, the MUs and PUs schedule different component carriers (CCs) according to different algorithms. For the MUs, an improved simulated annealing (SA) scheduling algorithm is proposed to maximize the sum rate of the MUs. Compared with the existing SA, the inner loop of the proposed SA is redesigned. Consequently, the best value can be obtained more quickly. For PUs, a location information based low-complexity maximize minimum distance (MMD) algorithm is proposed to reduce the interference from PBSs to PUs as much as possible. Overall, an integrated scheme is proposed to improve the performance. At last, numerical results demonstrate the performance of the proposed schemes.

Aiming at excessive users existing in a pico base station (PBS) of heterogeneous networks, the resource allocation problem of maximizing the total uplink throughput is investigated in this paper. By deploying a relay node with energy harvesting, some users of the PBS are transferred to the adjacent idle PBS. The resource allocation problem is formulated as an optimization problem. The objective is to maximize the total uplink throughput of users in the PBS under the constraints of the user's minimum data rate, the energy consumption, and transmission power of the relay node. The optimal solution is obtained by using the augmented Lagrange multiplier method. Simulation results show that the proposed method has higher throughput compared with the conventional method (i.e., some PBS users are transferred to the macro base station). Moreover, compared with the equal power method, the proposed method has an increase in terms of throughput to a certain degree.

In traditional half-duplex (HD) communication systems, the HD base station (BS) can transmit artificial noise (AN) to jam the eavesdroppers for securing the downlink (DL) communication. However, guaranteeing uplink (UL) transmission is not possible with an HD BS because HD BSs cannot jam the eavesdroppers during UL transmission. In this chapter, we investigate the resource allocation algorithm design for secure multiuser systems employing a full-duplex (FD) BS for serving multiple HD DL and UL users simultaneously. In particular, the FD BS transmits AN to guarantee the concurrent DL and UL communication security. We propose a multi-objective optimization framework to study two conflicting yet desirable design objectives, namely total DL transmit power minimization and total UL transmit power minimization. To this end, the weighted Tchebycheff method is adopted to formulate the resource allocation algorithm design as a multi-objective optimization problem (MOOP). The considered MOOP takes into account the quality-of-service (QoS) requirements of all legitimate users for guaranteeing secure DL and UL transmission in the presence of potential eavesdroppers. Thereby, secure UL transmission is enabled by the FD BS, which would not be possible with an HD BS. Although the considered MOOP is non-convex, we solve it optimally by semidefinite programming (SDP) relaxation. Simulation results not only unveil the trade-off between the total DL transmit power and the total UL transmit power, but also confirm that the proposed secure FD system can guarantee concurrent secure DL and UL transmission and provide substantial power savings over a baseline system.

Traditional cellular network standards require users downlink(DL) and uplink(UL) associated to the same BS. However, due to the power gap between BSs and users and different transmission environment(e.g. the path gain) of DL and UL, a serving BS with the strongest downlink would yield to a non-serving BS in the uplink. In this paper we propose the DL/UL splitting user association framework under a two-tier heterogeneous network, in which femtocell base stations are randomly located over a macro base station in a specific area. Downlink and Uplink network ergodic throughput are analysed according to our DL/UL splitting association model. Simulation results show a great throughput promotion compared with the traditional DL/UL coupled association manner. We believe downlink and uplink splitting as a flexible connection mode between users and base stations would be an essential approach to realize the high capacity requirements, which is a evolution of the network connection art.

Massive multiple input multiple output (MIMO) and full duplex (FD) communication are being considered as potential candidates for the spectrum efficient 5G wireless networks. In this paper, we develop a tractable model for downlink (DL) and uplink (UL) transmission in K-tier heterogeneous cellular networks (HCNs) with massive MIMO macrocells and full duplex (FD) small cells for spectrum efficiency. In the considered HCNs, the performance of the mobile user (MU) is limited by several sources of interference, specifically due to FD nature of small cell base stations (SBSs). A stochastic geometry based model of the proposed HCNs is provided which allows to derive the DL and UL rate coverage probabilities of such a system. Monte Carlo simulations confirm the accuracy of the analytical results, while numerical results reveal that equipping large number of MIMO antennas at macro base stations (MBSs) enhances the DL rate coverage probability of a random MU in HCNs. The results show that to achieve the maximum joint DL and UL performance gain in HCNs with FD small cells, both SBSs' density and SBSs' transmit power should be optimized. Moreover, the UL performance can be improved by decreasing the SBSs receivers sensitivity and increasing the UL power control factor.

This paper aims at studying user association for uplink (UL) transmission in cooperative heterogeneous cellular networks, where small cell sum rate is limited by the backhaul (BH) capacity. The investigated architecture can be modeled as a multiple-access relay channel (MARC) channel where multiple users communicate with a final destination (the macro base station) with the help of a relay (the small cell base station). A network-coding-based MARC, which exploits both the direct and relayed transmissions, is introduced to deal with low-capacity BH. We assess the UL average system capacity for 1) the baseline association based on the strongest reference signal received power (RSRP) in downlink (DL) and 2) the optimized user association chosen to improve the overall network UL sum-rate. Our results show that the network-coding-based MARC scheme achieves significant gains with respect to the pure relaying strategy. We further show that the optimized user association provides significant gains in network UL sum-rate with respect to the RSRP association, for the same sum power constraint and without degrading DL performance, especially when the BH capacity is sufficiently large.

NR5G dual connectivity (DC) with control/user (C/U)-plan split is the best capacity enhancing approach for high-speed users. In this work, we present DC-architecture with non-standalone (NSA) model of 5G network in which we consider LTE evolved Node Base station (eNBs) as macro base station and NR5G next-generation node Base station (gNBs) as micro base station. These macro eNB and micro gNBs are responsible for C/U-plan traffics respectively, so called EUTRAN(LTE)-NR5G dual connectivity (ENDC). We analyze the transition of C-plane or D-plane from the source network to the target network in the proposed HetNet i.e., Control-Plane Handoffs (CPHO), User-Plane Handoffs (UPHO). we evaluate the performance of ENDC C/U plan split in the shadowing environment for various range of user equipment (UE) velocities.KeywordsNR5G HetNetDual connectivity (DC)C/U-Plane splitControl Plane Handoffs (CPHO)User Plane Handoffs (UPHO)User Equipment (UE)eNB and gNB

In Heterogeneous networks (HetNets), the power difference between macro base stations (MBSs) and small base stations (SBSs) causes severe load unbalance. Therefore, cell range expansion (CRE) is proposed as an effective method to extend the coverage of SBSs and achieve balanced utilization of BSs. However, the downlink (DL) quality for offloaded user equipment (UE) cannot be guaranteed. In this paper, a traffic-aware user association scheme is proposed in HetNets. Distinct association biases are applied to different UEs according to their requirements. System performance of the proposed scheme is analyzed using the tool of stochastic geometry. The results show that the proposed scheme can improve DL throughput by enhancing the rate coverage of UEs, meanwhile signal-to-interference-plus-noise ratio (SINR) requirement with low data rate demand UEs is ensured. Moreover, the optimal association bias, which maximizes DL throughput, can be derived through particle swarm optimization (PSO), and it changes with different densities of BSs and UEs.

User association is a crucial factor that affects the performance of wireless networks. In current cellular networks, user association is typically coupled, which means an user equipment (UE) must associate with the same base station (BS) in uplink (UL) and downlink (DL). For single-tier wireless networks, such mechanism is simple and effective. However, in heterogeneous ultra-dense networks (UDNs), there are distinct differences in transmission power, data traffic and channel quality etc., for which coupled association could restrict the performance of system. To cope with it, the concept of decoupled UL-DL (DUDe) association has been introduced recently, which enables a UE to associate with different BSs in UL and DL. In this paper, we investigate decoupled UL-DL user association in UDNs. Considering the existence of asymmetric information (i.e., channel gains and intercell interferences), which can be seen as the private information for UE, we propose a contract-theoretic user association approach. Particularly, we model the decoupled association process as a monopoly labor market, where BSs act as employers and offer contracts to employees (i.e., UEs). The contract items cover the available associated bandwidths, transmitted powers and corresponding prices. Then BS broadcasts these drafted contract information, and UE selects to sign the optimal contract by considering her own demands. Numerical results show significant superiorities of DUDe than coupled UL-DL association in perspective of nodes utilities and social surplus, and compared with the existing user association methods, contract-theoretic approach shows a certain improvement in performance.

In this paper, we find the optimum lengths of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UL</sub> , T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DL</sub> and B i.e. the uplink (UL) and downlink (DL) pilots and feedback bits respectively maximizing the sum of the lower bounds of the UL and the DL rates. With the aid of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UL</sub> symbols, the Base Station (BS) estimates the UL channel of each user. T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DL</sub> symbols are means of estimating the downlink channel, which after being normalized and quantized with B bits, is made available at the BS. Estimated Channel State Information (CSI) and quantized Channel Direction Information (CDI), which may be received erroneously, are thus available at the BS for computing the receive and the transmit Zero-forcing (ZF) filters, respectively. The use of ZF enables the derivation of analytical DL and UL mean squared error (MSE) expressions that give a lower bound on the DL and UL rates, respectively, needed for our optimization.

To meet the subscribers ever increasing traffic demand, micro and macro base stations are being deployed excessively. As the traffic pattern varies according to the user's behavior, the deployment of micro and macro base stations plays a vital role in saving energy while maintaining the traffic demand of the subscribers. A macro base station consumes more than double the energy than a micro base station. Due to the space and time characteristics of the traffic, the BS cannot allocate resources effectively, which results in wasting energy consumption and low energy efficiency. Therefore, energy saving through deployment of base stations play a significant role to increase the energy efficiency. In this paper, the user traffic pattern is determined and the resources needed to fulfill the traffic are analyzed and finally the deployment strategies for the base stations are formulated.&#x0D; Since the base stations are fully loaded only for few hours a day, energy saving on the stations during low traffic will be significant. The energy saving schemes saved up to 18.8 % of energy in macro and 26.9 % of energy in micro BS. So, it would be more efficient to implement a heterogeneous network with more micro cells with energy saving schemes than just macro base stations.

Full duplex (FD) communication has emerged as an attractive solution for increasing the network throughput, by allowing downlink (DL) and uplink (UL) transmissions in the same spectrum. However, only employing FD base stations in heterogeneous cellular networks (HCNs) cause coverage reduction, due to the DL and UL interferences as well as the residual loop interference. We, therefore, propose HCNs with half duplex massive multiuser multiple-input multiple-output macrocell base stations (MBSs) to relax the coverage reduction, and FD small cell base stations (SBSs) to improve spectrum efficiency. A tractable framework of the proposed system is presented, which allows to derive exact and asymptotic expressions for the DL and the UL rate coverage probabilities, and the DL and the UL area spectral efficiencies (ASEs). Monte Carlo simulations confirm the accuracy of the analytical results, and it is revealed that the equipping massive number of antennas at MBSs enhances the DL rate coverage probability, whereas increasing FD SBSs increases the DL and the UL ASEs. The results also demonstrate that by tuning the UL fractional power control, a desirable performance in both UL and DL can be achieved.

Heterogeneous Networks (HetNets) have gained the attraction of the communication industry recently, due to their promising ability to enhance the performance of future broadband Fifth Generation (5G) networks and are integral parts of 5G systems. They can be viewed in multi-dimensional space where, each slice represents a unique tier that has its own Base Station (BS)s and User Equipment (UE)s. Different tiers cooperate with each other for their mutual benefit. Data can be interactively exchanged among the tiers, and UEs have the flexibility to switch between the tiers. The cells in such a heterogeneous cellular networks have variable sizes, shapes, and coverage regions. However, in HetNets with ultra dense BSs, the distance between them gets very small and, they suffer from very high levels of mutual interference. To improve the performance of HetNets, we have done multiple contributions in this dissertation. First, we have developed analytical derivations for optimizing pilot sequence length which is a very crucial factor in acquiring the Channel State Information (CSI) and the channel estimation process in general. Poisson Point Process (PPP) has been widely used to allocate BSs among various tiers so far. However, BS locations obtained using PPP approach may not be optimum to reduce interference. Therefore, in this dissertation, BSs locations are optimized to reduce the interference and improve the coverage and received signal power. Also, we have derived expressions for static UEs coverage probability and network energy efficiency in HetNets. A proper UE association algorithm for HetNets is a great challenge. The classic max-Signal to Interference and Noise Ratio (SINR) or max-received signal strength (RSS) user association algorithms are inappropriate solutions for HetNets as UEs in this context will tend to connect to the Macro BS, which is the one with the highest signal power. A severe load imbalance and significant inefficiency arises and impacts the performance. The aforementioned algorithms tend to associate UEs to BSs with the best received signal power or signal quality. In HetNets, usually Macro BSs are the ones transmitting the strongest signals; hence most UEs tend to associate with the Macro BS leaving Micro BSs with less load. Also, the conventional max-SINR and max-RSS algorithms do not provide adequate results in multi-tier systems. We suggest two centralized algorithms, LSTD and RTLB, for an even UE association to provide fair load distribution. However RTLB outperforms LSTD in real time scenarios as it easily and quickly adapts to rapid network changes. Furthermore, we consider the mobility of nodes. We derive coverage probability for moving UEs considering both handover and no handover scenarios. Proposed algorithms are fast enough to associate the moving users to different Micro and Macro BSs appropriately in real time. Our algorithms are proved to be feasible and provide a path towards attainable future communication systems.

Considering a two-tier HetNet adopting orthogonal frequency division multiple access (OFDMA) in downlink, we propose a multi-agent deep reinforcement learning (MA-DRL) scheme to perform channel assignment and power allocation. The goal is to jointly optimize the system capacity and power consumption. In the proposed scheme, the macro base station (MBS) and pico base stations (PBSs) play the role of agents. Each agent consists of a deep <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Q$</tex> network (DQN) and a deep deterministic policy gradient (DDPG) network performing channel assignment and power allocation in serial. Simulation results show that the proposed algorithm converges steadily and can be used to improve the system capacity and reduce the power consumption effectively.