Multiple Access Heterogeneous Networks Research Articles

Energy efficient resource allocation for uplink hybrid power domain sparse code nonorthogonal multiple access heterogeneous networks with statistical channel estimation

AbstractModern 5G heterogeneous networks (HetNets) require hybrid multiple access technology for optimal performance. The feasibility of a hybrid power domain sparse code nonorthogonal multiple access (PD‐SCMA) that integrates both power domain nonorthogonal multiple access (PD‐NOMA) and sparse code multiple access (SCMA) for an uplink hierarchical HetNet system is demonstrated. Hybrid schemes namely: Successive Codebook Ordering Assignment (SCOA) for codebook assignment (CA), opportunistic MUE‐SUE pairing (OMSP) for user pairing (UP), and a QoS‐aware power allocation (QAPA) for power allocation (PA) are developed. The SCOA algorithm is based on channel quality ordering metric, OMSP algorithm is based on channel quality diversity and pairing interference metric while the QAPA algorithm features a QoS awareness metric. A joint energy efficiency (EE) resource allocation (JEERA) algorithm that iteratively performs CA, UP, and PA for small cell user equipment (SUE) and the macro user equipment (MUE) to limit interference, improve spectral and energy efficiency is presented. The problem is formulated as a mixed integer nonconvex system EE resource allocation optimization for the small cells under QoS constraints of minimum sum‐rate, interference temperature, maximum power, and SCMA structure for a hybrid low complexity joint SIC‐Log‐MPA receiver. A modified near‐optimal dual decomposition analytical methodology featuring Dinkelbach fractional transformations is utilized to assess the system's performance on an imperfect wireless channel. Through numerical results, the proposed schemes are shown to improve the EE of the small cells in comparison with the prevalent schemes.

Hypergraph Spectral Clustering Based Spectrum Resource Allocation for Dense NOMA-HetNet

In this letter, we propose a spectrum resource allocation algorithm in non-orthogonal multiple access heterogeneous network (NOMA-HetNet). We consider a dense two-tier HetNet consisting multiple macro base station (MBS) and multiple femto base stations (FBSs), which are very close to each other. All the MBS and FBSs are working in NOMA mode. Our hypergraph spectral clustering based method is proposed to deal with the serious cumulative interference. We aim at improving the system throughput with the prerequisite that all users' fairness in the same base station is guaranteed. We analyze the computation complexity of the algorithm. The simulation result shows that our algorithm can improve the system throughput with low computational complexity.

Tier‐aware joint subchannel and power allocation in uplink OFDMA heterogeneous networks

AbstractWe study the problem of tier‐aware subchannel and power allocation in the uplink of a two‐tier orthogonal frequency‐division multiple access heterogeneous network. We formulate the joint subchannel and power allocation problem in the macro‐tier as an optimization problem that is aware of the existence of the femto‐tier and aims to maximize the sum of tolerable interference caused by femto‐tier on its allocated subchannel(s) subject to the minimum data rate requirements of the macrocell user equipments (MUEs). The resource allocation problem for the macro‐tier is an NP‐hard mixed‐integer nonlinear programming (MINLP) problem. To address it, we reformulate and transform it to a tractable mixed‐integer linear programming (MILP) problem, which is optimally addressed with polynomial‐time complexity. We formulate the joint subchannel and power allocation problem in the femto‐tier as an optimization problem that is aware of the existence of the macro‐tier and aims to maximize the sum rate of the femtocell user equipments subject to the maximum tolerable interference caused to the MUEs. To address this MINLP problem, we transform it to a MILP problem through a linear approximation, which is solved optimally by IBM CPLEX solver. In addition, we develop a distributed and efficient algorithm that addresses this optimization problem suboptimally with a lower computational complexity. Numerical results show that our proposed algorithms outperform the existing algorithms in terms of network sum rate.

Joint user association, subchannel assignment, and power allocation in full‐duplex OFDMA heterogeneous networks

AbstractIn‐band full‐duplex (FD) radio is regarded as a promising solution to enhance the spectral efficiency in the next‐generation wireless networks. In this paper, the problem of joint user association, subchannel assignment, and power allocation in FD orthogonal frequency‐division multiple access heterogeneous networks is considered. The weighted downlink and uplink sum rate of the network is maximized in a way that the transmit power of base stations and users remains below a given level. The problem is formulated as a nonconvex mixed‐integer nonlinear programming optimization problem. Then, it is converted into a suboptimal problem, which can be solved iteratively using difference of convex programming algorithm. Numerical results show that the proposed iterative algorithm converges quickly in few numbers of iterations with different initialization points. The results also show that the sum rate of an FD heterogeneous network can be as much as 66 % higher than the sum rate of a half‐duplex network.

Distributed Power Allocation for Nonorthogonal Multiple Access Heterogeneous Networks

In this letter, we investigate the power allocation problem in nonorthogonal multiple access (NOMA) heterogeneous networks (HetNets), where the macrocell base station (MBS) and small cell base station (SBS) compete to maximize their own throughput with minimum rate requirement of each user. The throughput of MBS and SBS is formulated based on the equivalent channel gain, and the power allocation problem is captured as a Stackelberg game. A distributed power allocation algorithm is proposed to achieve the Stackelberg equilibrium. Simulation results demonstrate the convergence of the proposed algorithm. Meanwhile, it is verified that the combination of NOMA and HetNets possesses great potential to improve the spectrum efficiency compared to the orthogonal multiple access based HetNets.

Removal of ICI and IBI in Wireless Heterogeneous Networks With Timing Misalignment

Since a small cell base station (SBS) of an orthogonal frequency division multiple access heterogeneous network (HetNet) does not intend to align arriving macrocell user signals, inter-carrier interference (ICI) and inter-block interference (IBI) inevitably arise in the uplink demodulation at the SBS. This letter proposes a novel precoding scheme based on interference alignment to remove the uplink ICI and IBI in a HetNet completely. The proposed scheme is able to remove the ceiling effect on the small cell uplink rate and increase the degrees of freedom of the system. Simulation results demonstrate the superiority of the scheme.

Dynamic femtocell resource allocation for managing inter‐tier interference in downlink of heterogeneous networks

This study investigates the downlink resource allocation problem in orthogonal frequency division multiple access heterogeneous networks consisting of macrocells and femtocells sharing the same frequency band. The focus is to devise optimised policies for femtocells' access to the shared spectrum, in terms of femtocell transmissions, in order to maximise femto-users (FUEs) sum data rate while ensuring that certain level of quality of service (QoS) for the macro-cell users in the vicinity of femtocells is provided. The optimal solution to this problem is obtained by employing the well-known dual Lagrangian method and the optimal femtocell transmit power and resource allocation solution is derived in detail. However, the optimal solution introduces high computational complexity. To this end, a heuristic solution to the problem is proposed. The algorithms to implement both optimal and efficient suboptimal schemes in a practical system are also given in detail while their complexity is compared. Simulation results show that proposed dynamic resource allocation scheme (a) ensures the macro-users QoS requirements compared with the Reuse-1 scheme, where femtocells are allowed to transmit at full power and bandwidth; (b) can maintain FUE data rates at high levels; (c) provides performance close to the optimal solution, while introducing much lower complexity.

Uplink radio resource allocation in orthogonal frequency‐division multiple access heterogeneous networks with limited feedback

Femtocell networks are expected to offer significant performance improvement with low cost. However, adaptive transmission based on maximising the sum rate of macro and femto networks requires perfect channel quality information (CQI) of the macro and femto links. This assumption requires an infinite resolution feedback link, which is not always practical since it requires an excessive amount of bandwidth. This study considers the problem of maximising average sum rate under the constraint of average maximum power transmission at macro and femto users. A suboptimal iterative algorithm is developed for finding the optimal CQI quantisers as well as the discrete power and rate at macro and femto transmitter for each quantised CQI level so as to maximise the average sum rate of the system. The author's numerical results give the number of bits required to sufficiently represent the CQI to achieve almost the maximum sum rate attained using full knowledge of the CQI.