Multicarrier Wireless Networks Research Articles

A Learning Approach for Low-Complexity Optimization of Energy Efficiency in Multicarrier Wireless Networks

This paper proposes computationally efficient algorithms to maximize the energy efficiency in multi-carrier wireless interference networks, by a suitable allocation of the system radio resources, namely the transmit powers and subcarrier assignment. The problem is formulated as the maximization of the system Global Energy-Efficiency subject to both maximum power and minimum rate constraints. This leads to a challenging non-convex fractional problem, which is tackled through an interplay of fractional programming, learning, and game theory. The proposed algorithmic framework is provably convergent and has a complexity linear in both the number of users and subcarriers, whereas other available solutions can only guarantee a polynomial complexity in the number of users and subcarriers. Numerical results show that the proposed method performs similarly as other, more complex, algorithms.

Resource Allocation With Minimum Outage Probability in Multicarrier Multicast Systems

Several innovative applications are emerging that require significant multimedia data transmissions, which unfortunately, current communication systems struggle to provide. In this paper, we examine the high outage tendencies of conventional multimedia multicasting (CVM) due to the bottleneck imposed by the user with minimum signal-to-noise ratio (SNR) and we present a technique based on the statistical approximations of the amortized weighted averaging (AWG) of users’ SNR. For completeness, we propose a suboptimal multicast resource allocation algorithm using memoization with stochastic rounding. We compare the system performance of AWG scheme with the CVM scheme in multicarrier wireless network using our newly derived system outage probability and average throughput as performance metrics. Numerical results not only show that the performance gap of our suboptimal algorithm is reasonably within 10% from the optimal solution, but also show that the AWG scheme admits more users and is more energy efficient than the CVM especially when low power is available to the system.

Frequency-code domain contention in multi-antenna multicarrier wireless networks

Coordination among users is an inevitable but time-consuming operation in wireless networks. It severely limit the system performance when the data rate is high. We present FC-MAC, a novel MAC protocol that can complete a contention within one contention slot over a joint frequency-code domain. When a node takes part in the contention, it generates randomly a contention vector (CV), which is a binary sequence of length equal to the number of available orthogonal frequency division multiplexing (OFDM) subcarriers. In FC-MAC, different user is assigned with a distinct signature (i.e., PN sequence). A node sends the signature at specific subcarriers and uses the sequence of the ON/OFF states of all subcarriers to indicate the chosen CV. Meanwhile, every node uses the redundant antennas to detect the CVs of other nodes. The node with the minimum CV becomes the winner. The experimental results show that, the collision probability of FC-MAC is as low as 0.05% when the network has 100 nodes. In comparison with IEEE 802.11, contention time is reduced by 50–80% and the throughput gain is up to 200%.

Generalized Cross-Layer Designs for Generic Half-Duplex Multicarrier Wireless Networks With Frequency-Reuse

In this paper, joint designs of data routes and resource allocations are developed for generic half-duplex multicarrier wireless networks in which each subcarrier can be reused by multiple links. Two instances are considered. The first instance pertains to the general case in which each subcarrier can be timeshared by multiple links, whereas the second instance pertains to a special case in which time-sharing is not allowed and a subcarrier, once assigned to a set of links, is used by those links throughout the signalling interval. Novel frameworks are developed to optimize the joint design of data routes, subcarrier schedules and power allocations. These design problems are nonconvex and hence difficult to solve. To circumvent this difficulty, efficient techniques based on geometric programming are developed to obtain locally optimal solutions. Numerical results show that the designs developed in both instances yield performance that is superior to that of their counterparts in which frequency-reuse is not allowed.

Adaptive and Generic Scheduling Scheme for LTE/LTE-A Mobile Networks

Schedulers for multi-carrier wireless networks are a central element of cellular systems and are subject to extensive research. However, state-of-the-art schedulers are hardly implementable in a real system such as long term evolution advanced (LTE-A), which imposes additional constraints on how resources are allocated. To address this problem, we first propose adaptive and generic scheduling scheme (AGSS) a generic resource allocation procedure that enables the implementation of state-of-the-art scheduling policies for building a LTE scheduler. In a second step, we propose our own scheduling policy called opportunistic PDOR aware (OPA) that both optimizes the use of the radio spectrum and provides the quality of service actually expected by applications. We show how to implement this policy using our generic scheduling scheme. We then compare the performance of AGSS to the classic scheme in a LTE environment when used with a given policy. We show that the proposed scheme outperforms the classic scheme whatever the policy. We also establish that OPA offers the best performances in terms of capacity and quality of service compared to state-of-the-art policies.

Price‐based spectrum sharing and rate allocation in the downlink of multihop multicarrier wireless networks

The author addresses the problem of subcarrier sharing with discrete rate allocation in the downlink of multicell and multihop orthogonal frequency division multiple access networks. The co-channel interference makes the problem computationally intractable. The author therefore models the problem as a non-cooperative game among the transmitting nodes with smaller scale problems. Each problem is solved using dual decomposition. Moreover, to mitigate the degradation effect of co-channel interference in this game, the author additionally proposes a price-based game. This game charges the nodes for their transmit power on subcarriers. Numerical results demonstrate that price-based game outperforms the non-cooperative game as a result of distributed interference avoidance. In addition, both the games with subcarrier sharing achieve higher sum-rate in comparison with resource allocation schemes with no subcarrier sharing.

Pre-Equalization in the Downlink of a Multicarrier Wireless Network Under Utility and Sum-Rate Optimization

This paper studies the problem of downlink pre-equalization in a multicarrier wireless network under utility and sum-rate maximization. The network utility depends on two main factors: an efficiency mapping which is a function of the signal-to-interference-noise ratio (SINR), and the power of the pre-equalization variables. Meanwhile, the sum-rate index is constructed by the summation of a logarithmic function of the SINRs of the active users. The network utility and sum-rate maximization problems are formulated here by assuming that the data estimation at the mobile units (MUs) is carried out by a simple matched filter. The optimal solutions are derived in this work for the pre-equalization factors by following a strategy that is distributed with respect to the channel state information (CSI) and data rates, but centralized with respect to the spreading sequences of all active users. The construction of these optimal solutions requires in each case a two step procedure. First, the optimal SINR is computed for the maximum utility and sum-rate solutions based on the efficiency mapping and on the bound of the transmission power, respectively. Then, exploiting the induced diversity by the multiple subcarriers, the pre-equalization algorithms cancel the multiple-access interference (MAI) and channel distortions, minimize the transmission power and achieve the optimal SINR after signal detection. A comprehensive numerical evaluation is presented at the end of the paper to validate the analytical derivations. Applications of the proposed pre-equalization schemes could be associated among others to cellular communication systems, and wireless networks of actuators.

Joint Access Point Selection and Power Allocation for Uplink Wireless Networks

We consider the distributed uplink resource allocation problem in a multi-carrier wireless network with multiple access points (APs). Each mobile user can optimize its own transmission rate by selecting a suitable AP and by controlling its transmit power. Our objective is to devise suitable algorithms by which mobile users can jointly perform these tasks in a distributed manner. Our approach relies on a game theoretic formulation of the joint power control and AP selection problem. In the proposed game, each user is a player with an associated strategy containing a discrete variable (the AP selection decision) and a continuous vector (the power allocation among multiple channels). We provide characterizations of the Nash Equilibrium of the proposed game, and present a set of novel algorithms that allow the users to efficiently optimize their rates. Finally, we study the properties of the proposed algorithms as well as their performance via extensive simulations.

Feedback-Driven Interactive Learning in Dynamic Wireless Resource Management for Delay-Sensitive Users

In this paper, we study the problem of dynamic resource management for delay-sensitive users over wireless networks. We focus on a decentralized setting, where autonomous users make self-interested decisions to maximize their utility functions as evaluated based on information feedback. In this paper, two types of information feedback are discussed. One is the private information feedback between a transmitter-receiver pair. The other is the public information feedback among users (i.e., different transmitter-receiver pairs). Due to the informationally decentralized nature of the wireless network, a user cannot have complete information about the transmission actions of its interfering neighbors. However, the user can implicitly or explicitly model the transmission strategies of its major interference sources based on the information feedback. In this paper, we provide an interactive learning framework for distributed power control of delay-sensitive users over multicarrier wireless networks. Specifically, the user can adopt corresponding interactive learning schemes to explicitly model the other users' strategies if public information feedback is available or to implicitly model the impact of other users' actions on its utility if only private information is available. Based on these models, the user creates beliefs and is able to strategically adapt its decisions to maximize its utility. We determine the performance upper bounds for the user's utility when learning from private or public information feedback and investigate the cost-performance tradeoffs resulting from the information feedback gathered with different frequencies and from various users. The simulation results show that the proposed adaptive interactive learning approach significantly improves the energy efficiency of delay-sensitive users compared with schemes that perform myopic best response.

Carrier assignment algorithms for OFDM-based multi-carrier wireless networks with channel adaptation

We study carrier assignment in a single-cell multiuser OFDM multi-carrier system so as to satisfy user rate requirements with minimal resources. Different users experience different quality in different carriers due to frequency selectivity of users' propagation channels and due to non-co-located user receivers that perceive different interference from neighboring cells across carriers. We study a static instance of the problem, specified by user carrier qualities and rate requirements. Adaptive modulation at the transmitter differentiates carriers for each user. In good quality carriers, the user satisfies per-frame rate requirements with few slots (or equivalently it satisfies its per-slot rate requirements with small occupied time slot portion). We study integral and fractional assignment, where a user is assigned to only one or several carriers. Fractional assignment is formulated as a linear programming problem. For integral assignment, we introduce two classes of iterative heuristics that use carrier reassignment to users and user substitution in carriers respectively and may be viewed as resulting from corresponding optimal fractional assignment algorithms. We use Lagrangian relaxation to obtain performance bounds and show that the two classes of heuristics arise from two relaxations. Our approach identifies efficient feasible solutions and is amenable to distributed implementation.

Throughput analysis in wireless networks with multiple users and multiple channels

We consider the problem of maximizing throughput in a multi-carrier wireless network that employs predictive link adaptation. We explicitly consider the time-penalty incurred due to link adaptation. The contributions of this paper are twofold. Firstly, several high performance algorithms (offline and online) are developed for efficient performance in multiple user and multiple channel environment under the practicable lookahead prediction of one time slot. Secondly, the presented algorithms and heuristics are shown to be competitive by deterministic and probabilistic analyses. Our results show that a modest consumption of resources for channel prediction and link adaptation may result in a significant throughput improvement.