FAST Copper for Broadband Access

FAST Copper is a multi-year, U.S. NSF funded project that started in 2004, and is jointly pursued by the research groups of Mung Chiang at Princeton University, John Cioffi at Stanford University, and Alexander Fraser at Fraser Research Lab, and in collaboration with several industrial partners including AT&T. The goal of the FAST Copper Project is to provide ubiquitous, 100 Mbps, fiber/DSL broadband access to everyone in the US with a phone line. This goal will be achieved through two threads of research: dynamic and joint optimization of resources in Frequency, Amplitude, Space, and Time (thus the name 'FAST') to overcome the attenuation and crosstalk bottlenecks, and the integration of communication, networking, computation, modeling, and distributed information management and control for the multi-user twisted pair network

Iterative Spectrum Balancing for Digital Subscriber Lines

Dynamic spectrum management (DSM) is an important technique for mitigating crosstalk in DSL. One of the first DSM algorithms proposed, Iterative waterfilling (IW), has a low complexity and demonstrates the spectacular performance gains that are possible. Unfortunately IW tends to be highly suboptimal in mixed CO/RT deployments and upstream VDSL. Another DSM algorithm, Optimal spectrum balancing (OSB), uses a weighted rate-sum to find the theoretically optimal transmit spectra. Unfortunately its complexity scales exponentially with the number of lines in the binder N. Typical binders contain 25-100 lines, for which OSB is intractable. This paper presents a new iterative algorithm for spectrum management in DSL. The algorithm optimizes the weighted rate-sum in an iterative fashion, which leads to a quadratic, rather than exponential, complexity in N. The algorithm is tractable for large N and can be used to optimize entire binders. Simulations show that the algorithm performs very close to the theoretical optimum achieved by OSB

Multi-User Signal and Spectra Coordination for Digital Subscriber Lines

The appetite amongst consumers for ever higher data-rates seems insatiable. This booming market presents a huge opportunity for telephone and cable operators. It also presents a challenge: the delivery of broadband services to millions of customers across sparsely populated areas. Fully fibre-based networks, whilst technically the most advanced solution, are prohibitively expensive to deploy. Digital subscriber lines (DSL) provide an alternative solution. Seen as a stepping-stone to a fully fibre-based network, DSL operates over telephone lines that are already in place, minimizing the cost of deployment. The basic principle behind DSL technology is to increase data-rate by widening the transmission bandwidth. Unfortunately, operating at high frequencies, in a medium originally designed for voice-band transmission, leads to crosstalk between the different DSLs. Crosstalk is typically 10-15 dB larger than the background noise and is the dominant source of performance degradation in DSL. This thesis develops practical multi-user techniques for mitigating crosstalk in DSL. The techniques proposed have low complexity, low latency, and are compatible with existing customer premises equipment (CPE). In addition to being practical, the techniques also yield near-optimal performance, operating close to the theoretical multi-user channel capacity. Multi-user techniques are based on the coordination of the different users in a network, and this can be done on either a spectral or signal level

Performance Enhancement in Copper Twisted Pair Cable Communications

The thesis focuses on the area of copper twisted pair based wireline communications. As one of the most widely deployed communication media, the copper twisted pair cable plays an important role in the communication network cabling infrastructure. This thesis looks to exploit diversity to improve twisted pair channels for data communications in two common application areas, namely Ethernet over Twisted Paris and digital subscriber line over twisted pair based telephone network. The first part of the thesis addresses new approaches to next generation Ethernet over twisted pair cable. The coming challenge for Ethernet over twisted pair cable is to realise a higher data rate beyond the 25/40GBASE-T standard, in relatively short reach scenarios. The straight-forward approaches, such as improving cable quality and extending frequency bandwidth, are unlikely to provide significant improvement in terms of data rate. However, other system diversities, such as spectrum utilization are yet to be fully exploited, so as to meet the desired data rate performance. The current balanced transmission over the structured twisted pair cable and its parallel single-in-single-out channel model is revisited and formulated as a full-duplex multiple-in-multiple-out (MIMO) channel model. With a common ground (provided by the cable shield), the balanced transmission is converted into unbalanced transmission, by replacing the differential-mode excitation with single-ended excitation. In this way, MIMO adoption may offer spectrum utilization advantages due to the doubled number of the channels. The S-parameters of the proposed MIMO channel model is obtained through the full wave electromagnetic simulation of a short CAT7A cable. The channel models are constructed from the resulting S-parameters, also the corresponding theoretical capacity is evaluated by exploiting different diversity scenarios. With higher spectrum efficiency, the orthogonal-frequency-division-multiplexing (OFDM) modulation can significantly improve the theoretical capacity compared with single-carrier modulation, where the channel frequency selectivity is aided. The MIMO can further enhance the capacity by minimising the impact of the crosstalk. When the crosstalk is properly handled under the unbalanced transmission, this thesis shows that the theoretical capacity of the EoTP cable can reach nearly 200GBit/s. In order to further extend the bandwidth capability of twisted pair cables, Phantom Mode transmission is studied, aiming at creating more channels under balanced transmission operation. The second part of the thesis focuses on the research of advanced scheduling algorithms for VDSL2 QoS enhancement. For VDSL2 broadband access networks, multi-user optimisation techniques have been developed, so as to improve the basic data rate performance. Spectrum balancing improves the network performance by optimising users transmit power spectra as the resource allocation, to mitigate the impact from the crosstalk. Aiming at enhancing the performance for the upstream VDSL2 service, where the users QoS demand is not known by all other users, a set of autonomous spectrum balancing algorithms is proposed. These optimise users transmit power spectra locally with only direct channel state information. To prevent selfish behaviour, the concept of a virtual user is introduced to represent the impact on both crosstalk interference and queueing status of other users. Moreover, novel algorithms are developed to determine the parameters and the weight of the virtual user. Another type of resource allocation in the VDSL2 network is crosstalk cancellation by centralised signal coordination. The history of the data queue is considered as a time series, on which different smooth filter characteristics are investigated in order to investigate further performance improvement. The use of filter techniques accounts for both the instantaneous queue length and also the previous data to determine the most efficient dynamic resource allocation. With the help of this smoothed dynamic resource allocation, the network will benefit from both reduced signalling communication and improved delay performance.The proposed algorithms are verified by numerical experiments

Distributed power allocation for D2D communications underlaying/overlaying OFDMA cellular networks

The implementation of device-to-device (D2D) underlaying or overlaying pre-existing cellular networks has received much attention due to the potential of enhancing the total cell throughput, reducing power consumption and increasing the instantaneous data rate. In this paper we propose a distributed power allocation scheme for D2D OFDMA communications and, in particular, we consider the two operating modes amenable to a distributed implementation: dedicated and reuse modes. The proposed schemes address the problem of maximizing the users' sum rate subject to power constraints, which is known to be nonconvex and, as such, extremely difficult to be solved exactly. We propose here a fresh approach to this well-known problem, capitalizing on the fact that the power allocation problem can be modeled as a potential game. Exploiting the potential games property of converging under better response dynamics, we propose two fully distributed iterative algorithms, one for each operation mode considered, where each user updates sequentially and autonomously its power allocation. Numerical results, computed for several different user scenarios, show that the proposed methods, which converge to one of the local maxima of the objective function, exhibit performance close to the maximum achievable optimum and outperform other schemes presented in the literature

A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications

Despite the numerous benefits brought by Device-to-Device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of User Equipments (UEs). Most of the previous studies mainly focus on how to maximize the Spectral Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we study how to maximize each UE's Energy Efficiency (EE) in an interference-limited environment subject to its specific Quality of Service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. A distributed interference-aware energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. We prove that the optimum solution obtained by the proposed algorithm is the Nash equilibrium of the noncooperative game. We also analyze the tradeoff between EE and SE and derive closed-form expressions for EE and SE gaps.Comment: submitted to IET Communications. arXiv admin note: substantial text overlap with arXiv:1405.1963, arXiv:1407.155

Joint Spectrum and Power Allocation for D2D Communications Underlaying Cellular Networks

This paper addresses the joint spectrum sharing and power allocation problem for device-to-device (D2D) communications underlaying a cellular network (CN). In the context of orthogonal frequency-division multiple-access systems, with the uplink resources shared with D2D links, both centralized and decentralized methods are proposed. Assuming global channel state information (CSI), the resource allocation problem is first formulated as a nonconvex optimization problem, which is solved using convex approximation techniques. We prove that the approximation method converges to a suboptimal solution and is often very close to the global optimal solution. On the other hand, by exploiting the decentralized network structure with only local CSI at each node, the Stackelberg game model is then adopted to devise a distributed resource allocation scheme. In this game-theoretic model, the base station (BS), which is modeled as the leader, coordinates the interference from the D2D transmission to the cellular users (CUs) by pricing the interference. Subsequently, the D2D pairs, as followers, compete for the spectrum in a noncooperative fashion. Sufficient conditions for the existence of the Nash equilibrium (NE) and the uniqueness of the solution are presented, and an iterative algorithm is proposed to solve the problem. In addition, the signaling overhead is compared between the centralized and decentralized schemes. Finally, numerical results are presented to verify the proposed schemes. It is shown that the distributed scheme is effective for the resource allocation and could protect the CUs with limited signaling overhead

Joint Resource Optimization for Multicell Networks with Wireless Energy Harvesting Relays

This paper first considers a multicell network deployment where the base station (BS) of each cell communicates with its cell-edge user with the assistance of an amplify-and-forward (AF) relay node. Equipped with a power splitter and a wireless energy harvester, the self-sustaining relay scavenges radio frequency (RF) energy from the received signals to process and forward the information. Our aim is to develop a resource allocation scheme that jointly optimizes (i) BS transmit powers, (ii) received power splitting factors for energy harvesting and information processing at the relays, and (iii) relay transmit powers. In the face of strong intercell interference and limited radio resources, we formulate three highly-nonconvex problems with the objectives of sum-rate maximization, max-min throughput fairness and sum-power minimization. To solve such challenging problems, we propose to apply the successive convex approximation (SCA) approach and devise iterative algorithms based on geometric programming and difference-of-convex-functions programming. The proposed algorithms transform the nonconvex problems into a sequence of convex problems, each of which is solved very efficiently by the interior-point method. We prove that our algorithms converge to the locally optimal solutions that satisfy the Karush-Kuhn-Tucker conditions of the original nonconvex problems. We then extend our results to the case of decode-and-forward (DF) relaying with variable timeslot durations. We show that our resource allocation solutions in this case offer better throughput than that of the AF counterpart with equal timeslot durations, albeit at a higher computational complexity. Numerical results confirm that the proposed joint optimization solutions substantially improve the network performance, compared with cases where the radio resource parameters are individually optimized