S. M. Ahsan Kazmi

Power Control for Interference Management and QoS Guarantee in Heterogeneous Networks

We consider the sum-rate optimization problem with power control for uplink transmission in a heterogeneous network (HetNet) consisting of a macrocell and multiple femtocells. The considered problem includes the HetNets crucial constraints of both cross-tier interference protection and user QoS in terms of outage probability and average delay. We transform the original nonconvex problem into a convex problem and develop a distributed algorithm that can attain the global optimal transmit power values. This algorithm, however, has heavy network overheads, which may lead to increased energy consumption for femtocell user equipment. We propose a new practical near-optimal distributed algorithm that eliminates these network overheads. Numerical results show that the schemes have nearly identical performance.

Optimized Resource Management in Heterogeneous Wireless Networks

The dense and pervasive deployment of wireless small cells can boost the performance of existing macrocellular networks; however, it poses significant challenges pertaining to the cross-tier interference management. In this letter, the downlink resource allocation problem for an underlay small cell network is studied. In this network, the protection of the macrocell tier is achieved by imposing cross-tier interference constraints in the resource allocation problem. To solve the underlying mixed-integer resource allocation problem, we propose two different algorithms. The first algorithm is developed by applying the duality-based optimization approach for the relaxed problem, which enables distributed implementation. The second distributed algorithm, which enables coordination is devised based on matching theory. Simulation results show that the proposed duality-based algorithm outperforms the greedy approach by 4% in terms of sum-rate whereas the matching-based algorithm with tier-coordination yields performance gains up to 17% compared with the duality-based approach.

Mode Selection and Resource Allocation in Device-to-Device Communications: A Matching Game Approach

Device to device (D2D) communication is considered as an effective technology for enhancing the spectral efficiency and network throughput of existing cellular networks. However, enabling it in an underlay fashion poses a significant challenge pertaining to interference management. In this paper, mode selection and resource allocation for an underlay D2D network is studied while simultaneously providing interference management. The problem is formulated as a combinatorial optimization problem whose objective is to maximize the utility of all D2D pairs. To solve this problem, a learning framework is proposed based on a problem-specific Markov chain. From the local balance equation of the designed Markov chain, the transition probabilities are derived for distributed implementation. Then, a novel two phase algorithm is developed to perform mode selection and resource allocation in the respective phases. This algorithm is then shown to converge to a near optimal solution. Moreover, to reduce the computation in the learning framework, two resource allocation algorithms based on matching theory are proposed to output a specific and deterministic solution. The first algorithm employs the one-to-one matching game approach whereas in the second algorithm, the one-to many matching game with externalities and dynamic quota is employed. Simulation results show that the proposed framework converges to a near optimal solution under all scenarios with probability one. Moreover, our results show that the proposed matching game with externalities achieves a performance gain of up to 35 percent in terms of the average utility compared to a classical matching scheme with no externalities.

Coordinated Resource Partitioning and Data Offloading in Wireless Heterogeneous Networks

In this letter, a game-theoretic framework is proposed for coordinating resource partitioning and data offloading in LTE-based heterogeneous networks (HetNets). The goal of this framework is to determine the amount of radio resources a macrocell should offer to neighboring small cells (SCs) and the amount of traffic each SC should admit from the macrocell. A two-stage Stackelberg game is applied to optimize the strategies of both the macrocell (the leader) and SCs (the followers). The macrocells strategy is shown to be a mixed-boolean nonlinear program, which is NP-hard. To solve this problem efficiently, a branch and bound based method is proposed to obtain the global optimal. We also show that this two-stage game has a unique Stackelberg equilibrium. Numerical results show that the proposed framework outperforms the traditional design by 50% in term of offloaded data. Additionally, reduction of 14% was observed in term of cost paid by MBS.

Network economics approach to data offloading and resource partitioning in two-tier LTE HetNets

In two-tier LTE heterogeneous networks (HetNets), picocells can be offered radio resource in order to mitigate interference to picocell users in downlink transmission from high-power macrocell base station (MBS). This becomes important in order to maintain efficient operation of the network and generate benefit tradeoff between macrocell and picocells. In this paper, we propose a game based approach for joint resource partitioning and data offloading scheme to determine the amount of radio resource a MBS should offer to picocells and to determine how much traffic each picocell access point (AP) should admit from MBS. In our proposal, a two-stage Stackelberg game theory is applied to optimize the strategies of both MBS and APs in order to maximize both of their utilities and this scheme is implemented using the notion of Almost Blank Subframes (ABS) proposed in the LTE standard.

Decentralized spectrum allocation in D2D underlying cellular networks

The proliferation of novel network access devices and demand for high quality of service by the end users are proving to be insufficient and are straining the existing wireless cellular network capacity. An economic and promising alternate to enhance the spectral efficiency and network throughput is device to device (D2D) communication. However, enabling D2D communication poses significant challenges pertaining to the interference management. In this paper, we address the resource allocation problem for underlay D2D pairs. First, we formulate the resource allocation optimization problem with an objective to maximizes the throughput of all D2D pairs by imposing interference constraints for protecting the cellular users. Second, to solve the underlying mixed-integer non linear resource allocation problem, we propose a stable, self-organizing and distributed solution using matching theory. Finally, we simulate our proposition to validate the convergence, cellular user protection, and network throughput gains achieved by the proposal. Simulation results reveal that D2D pairs can achieve significant throughput gains (i.e., up to 45 - 91%) while protecting the cellular users compared to the scenario in which no D2D pairs exist.

SDN based optimal user association and resource allocation in heterogeneous cognitive networks

The increase in the number of connected smart mobile devices has fueled the exponential growth in mobile data. The next-generation networks must meet the demand for higher capacity. Heterogeneous cognitive networks with multiple base station tiers are a promising approach to achieving the higher data rate target. The user association problem is a major issue in the heterogeneous cognitive networks because of the disparity in transmission powers of the base stations involved. Our objective is to achieve the optimal user association under interference constraints. We formulate the problem into an optimization problem and employ matching theory to propose an algorithm to obtain the optimal user association. The proposed matching algorithm for the optimal user association plays the role of SDN application. We then perform simulations and compare our proposed algorithm with existing ones. The simulations results depict that our proposed algorithm outperforms others.

SDN Based Wireless Heterogeneous Network Management

The proliferation of novel network access devices and demand for high quality of service by the end users are proving to be insufficient for existing wireless heterogeneous networks, due to their inflexible and expensive equipment as well as complex and non-agile control plane. This article presents an architecture vision to address the challenges placed on future heterogeneous networks. Software defined networking is emerging as a solution for decoupling the control plane. Furthermore, it enables network function virtualization and network programmability which is very promising for meeting the high demands of end user. In this article, we present an SDN based management framework for cognitive heterogeneous networks. Moreover, we discuss the architectural changes, its control function and its interaction in detail. The proposed management framework enables optimal power control, resource allocation, interference management and provides end to end quality of service for its user.

Joint pricing and power allocation for uplink macrocell and femtocell cooperation

In this paper, we study cooperation among mobile users for uplink in two-tiers heterogeneous wireless networks. In our cooperative model, a macrocell user equipment can relay its data via a femtocell user equipment when it cannot connect to its macro base station or any femtocell base stations directly. In this scenario, the macrocell user equipment tries to find the best relay user in a set of candidate relay femtocell user equipments to maximize its utility function. Additionally, the candidate relay femtocell user equipments give a pricing-based strategy per each power unit to the macrocell user equipment along with power level at relay femtocell user equipments which would be used for relaying data in order to maximize both the relay femto and macrocell user equipments utility function. In static network environment, this problem is formulated as a Stackelberg game. Moreover, in stochastic network environment we find stochastic optimization in a long-term for both the utility functions by modeling the problem as a restless bandit problem. Simulation results illustrate the efficiency of our proposal.

ECCT: an efficient-cooperative ADHOC MAC for cluster-based TDMA system in VANETs

In VANETs, a clustering algorithm can be used to partition the network into smaller segments. Therefore, the clustering algorithms provide not only limited channel contention but also fair channel access within the cluster. In addition, they also increase spatial reuse in VANETs and efficient control for the network topology. The main concern in the clustering algorithm is the cluster stability. The major challenge is to elect a cluster head and to maintain the membership of member nodes in a highly dynamic and a fast-changing topology. Therefore, the major criterion for cluster formation is to form a stable cluster. In this paper, a clustering algorithm to affect organization and cooperative ADHOC MAC for cluster-based TDMA system in VANETs (ECCT) is proposed. The cooperation is used to help a cluster head update each neighbor clusters information which helps each cluster head to avoid collision when two clusters move into each others clusters transmission range. This efficiently utilizes a time slot. We use the lowest-ID algorithm to achieve organization. The analytical and simulated results show that not only the average number of time slots for electing a cluster head but also total number of time slots before data can be successfully transmitted is less than the existing cluster-based TDMA system and IEEE 802.11p.