Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Novel Intercell Interference Mitigation Algorithms for Multicell OFDMA Systems with Limited Base Station Cooperation

Resource allocation in multicell downlink orthogonal frequency division multiple-access (OFDMA) systems is investigated, where BSs first independently carry out subcarrier-allocation and then mitigate intercell interference (InterCI) with the aid of very limited base station (BS) cooperation. Two novel InterCI mitigation algorithms are proposed. The first one is the distributed decision making assisted cooperation (DDMC) algorithm, and the second one is the centralized decision making assisted cooperation (CDMC) algorithm. When employing the DDMC algorithm, each BS independently makes the InterCI mitigation decisions. By contrast, when employing the CDMC algorithm, the centralized InterCI mitigation decisions are made with the aid of the cell-edge users’ discrete InterCI information sharing among BSs. While both the algorithms motivate to maximize the spectral-efficiency (sum rate), the CDMC algorithm also aims to maximize the frequency reuse factor. In this paper, we study and compare the performance, including spectral-efficiency of cell-edge users, frequency reuse factor, overhead, etc., of the multicell downlink OFDMA systems employing the proposed and other InterCI mitigation algorithms. Our studies show that both the DDMC and CDMC algorithms can achieve better spectral-efficiency performance than the existing on-off power (OOP) algorithm. Moreover, the CDMC algorithm is capable of achieving the performance close to the upper-bound attained by the so-called full InterCI information assisted decision making (FIIDM) algorithm, which uses exhaustive search to determine the InterCI mitigation decisions. Additionally, the CDMC algorithm is demonstrated to have the highest frequency reuse factor in addition to its spectral-efficiency advantage

Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access

In this paper, we provide joint subcarrier assignment and power allocation schemes for quality-of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum-efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, we propose a dual-layer resource allocation approach and provide a complete solution using difference-of-two-concave-functions approximation, successive convex approximation, and gradient-search methods. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated in this case such that the macro-cell optimal RE and corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings

Joint User-Association and Resource-Allocation in Virtualized Wireless Networks

In this paper, we consider a down-link transmission of multicell virtualized wireless networks (VWNs) where users of different service providers (slices) within a specific region are served by a set of base stations (BSs) through orthogonal frequency division multiple access (OFDMA). In particular, we develop a joint BS assignment, sub-carrier and power allocation algorithm to maximize the network throughput, while satisfying the minimum required rate of each slice. Under the assumption that each user at each transmission instance can connect to no more than one BS, we introduce the user-association factor (UAF) to represent the joint sub-carrier and BS assignment as the optimization variable vector in the mathematical problem formulation. Sub-carrier reuse is allowed in different cells, but not within one cell. As the proposed optimization problem is inherently non-convex and NP-hard, by applying the successive convex approximation (SCA) and complementary geometric programming (CGP), we develop an efficient two-step iterative approach with low computational complexity to solve the proposed problem. For a given power-allocation, Step 1 derives the optimum userassociation and subsequently, for an obtained user-association, Step 2 find the optimum power-allocation. Simulation results demonstrate that the proposed iterative algorithm outperforms the traditional approach in which each user is assigned to the BS with the largest average value of signal strength, and then, joint sub-carrier and power allocation is obtained for the assigned users of each cell. Especially, for the cell-edge users, simulation results reveal a coverage improvement up to 57% and 71% for uniform and non-uniform users distribution, respectively leading to more reliable transmission and higher spectrum efficiency for VWN

Joint relay selection and bandwidth allocation for cooperative relay network

Cooperative communication that exploits multiple relay links offers significant performance improvement in terms of coverage and capacity for mobile data subscribers in hierarchical cellular network. Since cooperative communication utilizes multiple relay links, complexity of the network is increased due to the needs for efficient resource allocation. Besides, usage of multiple relay links leads to Inter- Cell Interference (ICI). The main objective of this thesis is to develop efficient resource allocation scheme minimizes the effect of ICI in cooperative relay network. The work proposed a joint relay selection and bandwidth allocation in cooperative relay network that ensures high achievable data rate with high user satisfaction and low outage percentage. Two types of network models are considered: single cell network and multicell network. Joint Relay Selection and Bandwidth Allocation with Spatial Reuse (JReSBA_SR) and Optimized JReSBA_SR (O_JReSBA_SR) are developed for single cell network. JReSBA_SR considers link quality and user demand for resource allocation, and is equipped with spatial reuse to support higher network load. O_JReSBA_SR is an enhancement of JReSBA_SR with decision strategy based on Markov optimization. In multicell network, JReSBA with Interference Mitigation (JReSBA_IM) and Optimized JReSBA_IM (O_JReSBA_IM) are developed. JReSBA_IM deploys sectored-Fractional Frequency Reuse (sectored- FFR) partitioning concept in order to minimize the effect of ICI between adjacent cells. The performance is evaluated in terms of cell achievable rate, Outage Percentage (OP) and Satisfaction Index (SI). The result for single cell network shows that JReSBA_SR has notably improved the cell achievable rate by 35.0%, with reduced OP by 17.7% compared to non-joint scheme at the expense of slight increase in complexity at Relay Node (RN). O_JReSBA_SR has further improved the cell achievable rate by 13.9% while maintaining the outage performance with reduced complexity compared to JReSBA_SR due to the effect of optimization. The result for multicell network shows that JReSBA_IM enhances the cell achievable rate up to 65.1% and reduces OP by 35.0% as compared to benchmark scheme. Similarly, O_JReSBA_IM has significantly reduced the RN complexity of JReSBA_IM scheme, improved the cell achievable rate up to 9.3% and reduced OP by 1.3%. The proposed joint resource allocation has significantly enhanced the network performance through spatial frequency reuse, efficient, fair and optimized resource allocation. The proposed resource allocation is adaptable to variation of network load and can be used in any multihop cellular network such as Long Term Evolution-Advanced (LTE-A) network