Admission Control and Network Slicing for Multi-Numerology 5G Wireless Networks

in IEEE Networking Letters (2020)

This letter studies the admission control and network slicing design for 5G New Radio (5G-NR) systems in which the total bandwidth is sliced to support the enhanced mobile broadband (eMBB) and ultra ... [more ▼]

This letter studies the admission control and network slicing design for 5G New Radio (5G-NR) systems in which the total bandwidth is sliced to support the enhanced mobile broadband (eMBB) and ultra reliable and low latency communication (URLLC) services. We allow traffic from the eMBB bandwidth part to be overflowed to the URLLC bandwidth part in a controlled manner. We develop a mathematical framework to analyze the blocking probabilities of both eMBB and URLLC services based on which the network slicing and admission control is jointly optimized to minimize the blocking probability of the eMBB traffic subject to the blocking probability constraint for the URLLC traffic. An efficient iterative algorithm is proposed to deal with the underlying problem. [less ▲]

Joint Data Compression and Computation Offloading in Hierarchical Fog-Cloud Systems

in IEEE Transactions on Wireless Communications (2019)

Data compression (DC) has the potential to significantly improve the computation offloading performance in hierarchical fog-cloud systems. However, it remains unknown how to optimally determine the ... [more ▼]

Data compression (DC) has the potential to significantly improve the computation offloading performance in hierarchical fog-cloud systems. However, it remains unknown how to optimally determine the compression ratio jointly with the computation offloading decisions and the resource allocation. This optimization problem is studied in this paper where we aim to minimize the maximum weighted energy and service delay cost (WEDC) of all users. First, we consider a scenario where DC is performed only at the mobile users. We prove that the optimal offloading decisions have a threshold structure. Moreover, a novel three-step approach employing convexification techniques is developed to optimize the compression ratios and the resource allocation. Then, we address the more general design where DC is performed at both the mobile users and the fog server. We propose three algorithms to overcome the strong coupling between the offloading decisions and the resource allocation. Numerical results show that the proposed optimal algorithm for DC at only the mobile users can reduce the WEDC by up to 65% compared to computation offloading strategies that do not leverage DC or use sub-optimal optimization approaches. The proposed algorithms with additional DC at the fog server lead to a further reduction of the WEDC. [less ▲]

Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges

in IEEE Communications Surveys and Tutorials (2018), 20(1), 674-707

Full-duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth ... [more ▼]

Full-duplex (FD) wireless technology enables a radio to transmit and receive on the same frequency band at the same time, and it is considered to be one of the candidate technologies for the fifth generation (5G) and beyond wireless communication systems due to its advantages, including potential doubling of the capacity and increased spectrum utilization efficiency. However, one of the main challenges of FD technology is the mitigation of strong self-interference (SI). Recent advances in different SI cancellation techniques, such as antenna cancellation, analog cancellation, and digital cancellation methods, have led to the feasibility of using FD technology in different wireless applications. Among potential applications, one important application area is dynamic spectrum sharing (DSS) in wireless systems particularly 5G networks, where FD can provide several benefits and possibilities such as concurrent sensing and transmission (CST), concurrent transmission and reception, improved sensing efficiency and secondary throughput, and the mitigation of the hidden terminal problem. In this direction, first, starting with a detailed overview of FD-enabled DSS, we provide a comprehensive survey of recent advances in this domain. We then highlight several potential techniques for enabling FD operation in DSS wireless systems. Subsequently, we propose a novel communication framework to enable CST in DSS systems by employing a power control-based SI mitigation scheme and carry out the throughput performance analysis of this proposed framework. Finally, we discuss some open research issues and future directions with the objective of stimulating future research efforts in the emerging FD-enabled DSS wireless systems. [less ▲]

Uplink/downlink matching based resource allocation for full-duplex OFDMA wireless cellular networks

in 2017 IEEE Wireless Communications and Networking Conference (WCNC) proceedings (2017, March 19)

In this paper, we study the resource allocation problem for a full-duplex (FD) multiuser wireless system consisting of one FD base-station (BS) and multiple FD mobile nodes. Our main focus is to jointly ... [more ▼]

In this paper, we study the resource allocation problem for a full-duplex (FD) multiuser wireless system consisting of one FD base-station (BS) and multiple FD mobile nodes. Our main focus is to jointly optimize the power allocation (PA) and subcarrier assignment (SA) for both uplink (UL) and downlink (DL) transmissions of all users to maximize the system sum-rate. Our design captures the self-interference of FD transceivers and allows the utilization of each subcarrier for multiple concurrent UP and DL transmissions. Since the joint optimization problem is a nonconvex mixed integer program, which is difficult to tackle, we propose to employ the bipartite matching method to address the SA. Toward this end, a fast greedy allocation algorithm is developed to perform initial assignment of UL/DL links to each subcarrier that offers the best sum rate. Then from the obtained SA solution, we adopt the successive convex approximation approach to solve the PA problem whose results are used to calculate the SA weights for re-optimizing the SA by using the bipartite matching method. We then present the numerical results to demonstrate the improvement of our proposed algorithm in comparison with the greedy FD and half-duplex (HD) resource allocation algorithms. [less ▲]

Coordinated Multipoint Transmission Design for Cloud-RANs With Limited Fronthaul Capacity Constraints

in IEEE Transactions on Vehicular Technology (2016), 65(9), 7432-7447

In this paper, we consider the coordinated multipoint (CoMP) transmission design for the downlink cloud radio access network (Cloud-RAN). Our design aims to optimize the set of remote radio heads (RRHs ... [more ▼]

In this paper, we consider the coordinated multipoint (CoMP) transmission design for the downlink cloud radio access network (Cloud-RAN). Our design aims to optimize the set of remote radio heads (RRHs) serving each user and the precoding and transmission power to minimize the total transmission power while maintaining the fronthaul capacity and users' quality-of-service (QoS) constraints. The fronthaul capacity constraint involves a nonconvex and discontinuous function that renders the optimal exhaustive search method unaffordable for large networks. To address this challenge, we propose two low-complexity algorithms. The first pricing-based algorithm solves the underlying problem through iteratively tackling a related pricing problem while appropriately updating the pricing parameter. In the second iterative linear-relaxed algorithm, we directly address the fronthaul constraint function by iteratively approximating it with a suitable linear form using a conjugate function and solving the corresponding convex problem. For performance evaluation, we also compare our proposed algorithms with two existing algorithms in the literature. Finally, extensive numerical results are presented, which illustrate the convergence of our proposed algorithms and confirm that our algorithms significantly outperform the state-of-the-art existing algorithms. [less ▲]

Computation capacity constrained joint transmission design for C-RANs

in 2016 IEEE Wireless Communications and Networking Conference proceedings (2016, April 03)

This paper considers the joint processing design for the cloud radio access network (C-RAN) with limited cloud computation capacity. This amounts to determine the set of remote radio heads (RRHs) serving ... [more ▼]

This paper considers the joint processing design for the cloud radio access network (C-RAN) with limited cloud computation capacity. This amounts to determine the set of remote radio heads (RRHs) serving each user and the corresponding precoding vectors whose corresponding computation effort (CE) is a non-linear function of the number of antennas pooled from all serving RRHs and the modulation bits. Toward this end, we propose a novel three-step approach to solve the underlying mixed non-linear integer program. First, we transform this problem into a group association problem (GAP) with additional association constraints where each user must be associated with exactly one particular group of RRHs. Second, we study the relaxed power minimization problem (PMP) where the group association integer variables are relaxed and the computational constraint functions are approximated by weighted linear functions of transmission powers. We prove that this relaxed PMP can be solved optimally and the obtained optimal solution satisfies all association constraints of the original GAP problem. Third, we develop an iterative procedure to update the weight parameters of the approximated computational constraint functions to drive the achieved solution to an efficient and feasible solution of the original problem. Finally, we present numerical results to demonstrate the significant gains of our proposed design compared to that due to a fast greedy algorithm. [less ▲]

Resource allocation optimization in multi-user multi-cell massive MIMO networks considering pilot contamination

in IEEE Access (2015), 3

In this paper, we study the joint pilot assignment and resource allocation for system energy efficiency (SEE) maximization in the multi-user and multi-cell massive multi-input multi-output network. We ... [more ▼]

In this paper, we study the joint pilot assignment and resource allocation for system energy efficiency (SEE) maximization in the multi-user and multi-cell massive multi-input multi-output network. We explicitly consider the pilot contamination effect during the channel estimation in the SEE maximization problem, which aims to optimize the power allocation, the number of activated antennas, and the pilot assignment. To tackle the SEE maximization problem, we transform it into a subtractive form, which can be solved more efficiently. In particular, we develop an iterative algorithm to solve the transformed problem where optimization of power allocation and number of antennas is performed, and then pilot assignment optimization is conducted sequentially in each iteration. To tackle the first sub-problem, we employ a successive convex approximation (SCA) technique to attain a solvable convex optimization problem. Moreover, we propose a novel iterative low-complexity algorithm based on the Hungarian method to solve the pilot assignment sub-problem. We also describe how the proposed solution approach can be useful to address the sum rate (SR) maximization problem. In addition to the algorithmic developments, we characterize the optimal structure of both SEE and SR maximization problems. The numerical studies are conducted to illustrate the convergence of the proposed algorithms, impacts of different parameters on the SR and SEE, and significant performance gains of the proposed solution compared the conventional design. [less ▲]

Sparse precoding design for cloud-RANs sum-rate maximization

in 2015 IEEE Wireless Communications and Networking Conference (WCNC) proceedings (2015, March 09)

This paper considers a sparse precoding design for sum-rate maximization in a cloud radio access network (Cloud-RAN). Constrained by the fronthaul link capacity and transmit power limit at each remote ... [more ▼]

This paper considers a sparse precoding design for sum-rate maximization in a cloud radio access network (Cloud-RAN). Constrained by the fronthaul link capacity and transmit power limit at each remote radio head (RRH), the sparse design amounts to determine the precoders at the RRHs as well as the set of serving RRHs for each mobile user. In this work, we first formulate the fronthaul link constraints as non-convex and discontinuous constraints with sparsity terms. These sparsity terms are then iteratively approximated into linear forms by means of reweighted ℓ1-norm with conjugate functions. Finally, to determine the beamforming vectors, the non-convex sum-rate maximization problem with linear constraints is transformed into an equivalent problem of iterative weighted mean-squared error minimization. Convergence of the proposed iterative algorithm is then proved and verified by the presented numerical results. In addition, numerical results demonstrate the superior performance by the proposed algorithm over a previously proposed one in literature. [less ▲]

Cooperative transmission in cloud RAN considering fronthaul capacity and cloud processing constraints

in 2014 IEEE Wireless Communications and Networking Conference (WCNC) proceedings (2014, September 06)

We investigate the cooperative transmission design for the cloud radio access network (C-RAN) considering fronthaul capacity and cloud processing constraints. Specifically, we consider the joint ... [more ▼]

We investigate the cooperative transmission design for the cloud radio access network (C-RAN) considering fronthaul capacity and cloud processing constraints. Specifically, we consider the joint transmission scheme where the baseband signals and precoding vectors are processed and calculated by the cloud, which are delivered over the fronthaul links to the remote radio heads (RRHs) to form the RF signals for being transmitted to the users. We formulate the joint optimization problem for precoding design and allocation of RRHs, fronthaul capacity, and BBU processing resources to minimize the total transmission power subject to QoS constraints of the users. We present both optimal exhaustive search algorithm and two low-complexity algorithms to solve the resource allocation problem where the first one can achieve the Pareto optimality and the second one can determine an efficient solution with pretty low complexity. Numerical results confirm the excellent performance of the proposed low-complexity algorithms. [less ▲]

Fair Resource Allocation for OFDMA Femtocell Networks With Macrocell Protection

in IEEE Transactions on Vehicular Technology (2014)

We consider the joint subchannel allocation and power control problem for orthogonal frequency-division multiple-access (OFDMA) femtocell networks in this paper. Specifically, we are interested in the ... [more ▼]

We consider the joint subchannel allocation and power control problem for orthogonal frequency-division multiple-access (OFDMA) femtocell networks in this paper. Specifically, we are interested in the fair resource-sharing solution for users in each femtocell that maximizes the total minimum spectral efficiency of all femtocells subject to protection constraints for the prioritized macro users. Toward this end, we present the mathematical formulation for the uplink resource-allocation problem and propose an optimal exhaustive search algorithm. Given the exponential complexity of the optimal algorithm, we develop a distributed and low-complexity algorithm to find an efficient solution for the problem. We prove that the proposed algorithm converges and we analyze its complexity. Then, we extend the proposed algorithm in three different directions, namely, downlink context, resource allocation with rate adaption for femto users, and consideration of a hybrid access strategy where some macro users are allowed to connect with nearby femto base stations (FBSs) to improve the performance of the femto tier. Finally, numerical results are presented to demonstrate the desirable performance of the proposed algorithms. [less ▲]