Rate Constrained Random Access over a Fading Channel

In this paper, we consider uplink transmissions involving multiple users communicating with a base station over a fading channel. We assume that the base station does not coordinate the transmissions of the users and hence the users employ random access communication. The situation is modeled as a non-cooperative repeated game with incomplete information. Each user attempts to minimize its long term power consumption subject to a minimum rate requirement. We propose a two timescale stochastic gradient algorithm (TTSGA) for tuning the users' transmission probabilities. The algorithm includes a 'waterfilling threshold update mechanism' that ensures that the rate constraints are satisfied. We prove that under the algorithm, the users' transmission probabilities converge to a Nash equilibrium. Moreover, we also prove that the rate constraints are satisfied; this is also demonstrated using simulation studies

SDN based Control and Management of WLANs in the 3GPP 5G Network

The exponential growth in mobile broadband usage [1] has catalyzed the need for high data rate communication systems. In this regard, activities for standardizing the next generation mobile broadband system, known as the Fifth Generation(5G) system are underway. The 5G system also enables the integration of Institute of Electrical and Electronic Engineers (IEEE) Wireless Local Area Networks (WLANs) for providing cost-effective broadband connectivity. It is therefore imperative to find solutions for control and management of WLANs, while providing seamless inter-working capabilities with the cellular network. In this paper, we propose a novel Software Defined Networking (SDN) based architecture for efficient control and management of IEEE WLANs while providing a mechanism for smooth integration of WLANs within the 5G system

Entropy-optimal Generalized Token Bucket Regulator

We derive the maximum entropy of a flow (information utility) which conforms to traffic constraints imposed by a generalized token bucket regulator, by taking into account the covert information present in the randomness of packet lengths. Under equality constraints of aggregate tokens and aggregate bucket depth, a generalized token bucket regulator can achieve higher information utility than a standard token bucket regulator. The optimal generalized token bucket regulator has a near-uniform bucket depth sequence and a decreasing token increment sequence.Comment: 6 pages (2 column, 10-point), 3 figures, 1 tabl

Performance and Energy Conservation of 3GPP IFOM Protocol for Dual Connectivity in Heterogeneous LTE-WLAN Network

For the 5th Generation (5G) networks, Third Generation Partnership Project (3GPP) is considering standardization of various solutions for traffic aggregation using licensed and unlicensed spectrum, to meet the rising data demands. IP Flow Mobility (IFOM) is a multi access connectivity solution/protocol standardized by the Internet Engineering Task force (IETF) and 3GPP in Release 10. It enables concurrent access for an User Equipment (UE) to Heterogeneous Networks (HetNets) such as Long Term Evolution (LTE) and IEEE 802.11 Wireless Local Area Network (WLAN). IFOM enabled UEs have multiple interfaces to connect to HetNets. They can have concurrent flows with different traffic types over these networks and can seamlessly switch the flows from one network to the other. In this paper, we focus on two objectives. First is to investigate the performance parameters e.g. throughput, latency, tunnelling overhead, packet loss, energy cost etc. of IFOM enabled UEs (IeUs) in HetNets of LTE and WLAN. We have proposed a novel mechanism to maximize the throughput of IeUs achieving a significant throughput gain with low latency for the IeUs. We have explored further and observed a throughput energy trade off for low data rate flows. To address this, we also propose a smart energy efficient and throughput optimization algorithm for the IeUs, resulting in a substantial reduction in energy cost, while maintaining the high throughput at lower latency and satisfying the Quality of Service (QoS) requirements of the IeUs.Comment: 12 pages, 15 figures, journa

Connecting the Unconnected: Towards Frugal 5G Network Architecture and Standardization

This article adopts a holistic approach to address the problem of poor broadband connectivity in rural areas by suggesting a novel wireless network architecture, also called the "Frugal 5G Network". To arrive at the Frugal 5G Network architecture, we take into consideration the rural connectivity needs and the characteristics specific to rural areas. As part of the proposed Frugal 5G Network, we define a heterogeneous Access Network wherein macro cells provide a carpet coverage while Wireless Local Area Networks (WLANs) provide additional capacity to serve the village clusters. WLAN is backhauled via a wireless network also called the wireless middle mile network. We define a Software Defined Networking (SDN) and Network Function Virtualization (NFV) based architecture to make the network flexible and scalable. The concepts of Fog computing have also been employed in the network architecture to bring intelligence to the edge, i.e., to the access network. Through a novel amalgamation of these technologies, we are able to address the connectivity requirements of rural areas. The proposed network architecture can serve as a potential solution towards IEEE P2061, a standardization project that aims to design an architecture to facilitate rural broadband communication

Multi-Player Multi-Armed Bandit Based Resource Allocation for D2D Communications

Device-to-device (D2D) communications is expected to play a significant role in increasing the system capacity of the fifth generation (5G) wireless networks. To accomplish this, efficient power and resource allocation algorithms need to be devised for the D2D users. Since the D2D users are treated as secondary users, their interference to the cellular users (CUs) should not hamper the CU communications. Most of the prior works on D2D resource allocation assume full channel state information (CSI) at the base station (BS). However, the required channel gains for the D2D pairs may not be known. To acquire these in a fast fading channel requires extra power and control overhead. In this paper, we assume partial CSI and formulate the D2D power and resource allocation problem as a multi-armed bandit problem. We propose a power allocation scheme for the D2D users in which the BS allocates power to the D2D users if a certain signal-to-interference-plus-noise ratio (SINR) is maintained for the CUs. In a single player environment a D2D user selects a CU in every time slot by employing UCB1 algorithm. Since this resource allocation problem can also be considered as an adversarial bandit problem we have applied the exponential-weight algorithm for exploration and exploitation (Exp3) to solve it. In a multiple player environment, we extend UCB1 and Exp3 to multiple D2D users. We also propose two algorithms that are based on distributed learning algorithm with fairness (DLF) and kth-UCB1 algorithms in which the D2D users are ranked. Our simulation results show that our proposed algorithms are fair and achieve good performance.Comment: 10 page

Performance Evaluation of Optimal Radio Access Technology Selection Algorithms for LTE-WiFi Network

A Heterogeneous Network (HetNet) comprises of multiple Radio Access Technologies (RATs) allowing a user to associate with a specific RAT and steer to other RATs in a seamless manner. To cope up with the unprecedented growth of data traffic, mobile data can be offloaded to Wireless Fidelity (WiFi) in a Long Term Evolution (LTE) based HetNet. In this paper, an optimal RAT selection problem is considered to maximize the total system throughput in an LTE-WiFi system with offload capability. Another formulation is also developed where maximizing the total system throughput is subject to a constraint on the voice user blocking probability. It is proved that the optimal policies for the association and offloading of voice/data users contain threshold structures. Based on the threshold structures, we propose algorithms for the association and offloading of users in LTE-WiFi HetNet. Simulation results are presented to demonstrate the voice user blocking probability and the total system throughput performance of the proposed algorithms in comparison to another benchmark algorithm

Resource Allocation for D2D Communications with Partial Channel State Information

Enhancement of system capacity is one of the objectives of the fifth generation (5G) networks in which device-to-device (D2D) communications is anticipated to play a crucial role. This can be achieved by devising efficient resource allocation strategies for the D2D users. While most of the works in resource allocation assume full knowledge of the channel states, transmitting it in every time slot reduces the system throughput due to extra control overhead and leads to wastage of power. In this paper, we address the problem of D2D resource allocation with partial channel state information (CSI) at the base station (BS) and ensure that the interference from the D2D users do not jeopardize the communications of cellular users (CUs). With partial CSI, existing algorithms determine the Nash equilibrium in a distributed manner, whose inefficiency in maximizing the social utility is well known as the players try to maximize their own utilities. This is the first work in the D2D resource allocation field in which within a game theoretic framework, an optimal D2D resource allocation algorithm is proposed which maximizes the social utility of the D2D players such that a social optimum is attained. Each D2D player with the help of the BS learns to select the optimal action. We consider the channel to exhibit path loss. Next, we consider both a slow and fast fading with CU mobility and propose two heuristic algorithms. We validate the performance of our proposed algorithms through simulation results

A Framework for Wireless Broadband Network for Connecting the Unconnected

A significant barrier in providing affordable rural broadband is to connect the rural and remote places to the optical Point of Presence (PoP) over distances of few kilometers. A lot of work has been done in the area of long distance Wi-Fi networks. However, these networks require tall towers and high gain (directional) antennas. Also, they work in the unlicensed band which has Effective Isotropically Radiated Power (EIRP) limit (e.g. 1 W in India) which restricts the network design. In this work, we propose a Long Term Evolution-Advanced (LTE-A) network operating in TV UHF to connect the remote areas to the optical PoP. In India, around 100 MHz of TV UHF band IV (470-585 MHz) is unused at any location and can be put to an effective use in these areas. We explore the idea of multi-hop topology for the proposed network. We also compare the performance of the multi-hop network with the Point to Multipoint (PMP) topology. The results show that multi-hop network performs much better than the PMP network. We then formulate a Linear Programming (LP) problem of generating optimal topology and compare its performance with the multi-hop network. Overall, the analysis implies that an optimally planned LTE-A network in TV UHF band can be a potential solution for affordable rural broadband

Power Efficient Scheduling under Delay Constraints over Multi-user Wireless Channels

In this paper, we consider the problem of power efficient uplink scheduling in a Time Division Multiple Access (TDMA) system over a fading wireless channel. The objective is to minimize the power expenditure of each user subject to satisfying individual user delay. We make the practical assumption that the system statistics are unknown, i.e., the probability distributions of the user arrivals and channel states are unknown. The problem has the structure of a Constrained Markov Decision Problem (CMDP). Determining an optimal policy under for the CMDP faces the problems of state space explosion and unknown system statistics. To tackle the problem of state space explosion, we suggest determining the transmission rate of a particular user in each slot based on its channel condition and buffer occupancy only. The rate allocation algorithm for a particular user is a learning algorithm that learns about the buffer occupancy and channel states of that user during system execution and thus addresses the issue of unknown system statistics. Once the rate of each user is determined, the proposed algorithm schedules the user with the best rate. Our simulations within an IEEE 802.16 system demonstrate that the algorithm is indeed able to satisfy the user specified delay constraints. We compare the performance of our algorithm with the well known M-LWDF algorithm. Moreover, we demonstrate that the power expended by the users under our algorithm is quite low.Comment: 14 pages, 14 figure