Distributed optimisation techniques for wireless networks

Alongside the ever increasing traffic demand, the fifth generation (5G) cellular network architecture is being proposed to provide better quality of service, increased data rate, decreased latency, and increased capacity. Without any doubt, the 5G cellular network will comprise of ultra-dense networks and multiple input multiple output technologies. This will make the current centralised solutions impractical due to increased complexity. Moreover, the amount of coordination information that needs to be transported over the backhaul links will be increased. Distributed or decentralised solutions are promising to provide better alternatives. This thesis proposes new distributed algorithms for wireless networks which aim to reduce the amount of system overheads in the backhaul links and the system complexity. The analysis of conflicts amongst transmitters, and resource allocation are conducted via the use of game theory, convex optimisation, and auction theory. Firstly, game-theoretic model is used to analyse a mixed quality of service (QoS) strategic non-cooperative game (SNG), for a two-user multiple-input single-output (MISO) interference channel. The players are considered to have different objectives. Following this, the mixed QoS SNG is extended to a multicell multiuser network in terms of signal-to-interference-and-noise ratio (SINR) requirement. In the multicell multiuser setting, each transmitter is assumed to be serving real time users (RTUs) and non-real time users (NRTUs), simultaneously. A novel mixed QoS SNG algorithm is proposed, with its operating point identified as the Nash equilibrium-mixed QoS (NE-mixed QoS). Nash, Kalai-Smorodinsky, and Egalitarian bargain solutions are then proposed to improve the performance of the NE-mixed QoS. The performance of the bargain solutions are observed to be comparable to the centralised solutions. Secondly, user offloading and user association problems are addressed for small cells using auction theory. The main base station wishes to offload some of its users to privately owned small cell access points. A novel bid-wait-auction (BWA) algorithm, which allows single-item bidding at each auction round, is designed to decompose the combinatorial mathematical nature of the problem. An analysis on the existence and uniqueness of the dominant strategy equilibrium is conducted. The BWA is then used to form the forward BWA (FBWA) and the backward BWA (BBWA). It is observed that the BBWA allows more users to be admitted as compared to the FBWA. Finally, simultaneous multiple-round ascending auction (SMRA), altered SMRA (ASMRA), sequential combinatorial auction with item bidding (SCAIB), and repetitive combinatorial auction with item bidding (RCAIB) algorithms are proposed to perform user offloading and user association for small cells. These algorithms are able to allow bundle bidding. It is then proven that, truthful bidding is individually rational and leads to Walrasian equilibrium. The performance of the proposed auction based algorithms is evaluated. It is observed that the proposed algorithms match the performance of the centralised solutions when the guest users have low target rates. The SCAIB algorithm is shown to be the most preferred as it provides high admission rate and competitive revenue to the bidders

Auction based competition of hybrid small cells for dropped macrocell users

We propose an auction based beamforming and user association algorithm for a wireless network consisting of a macrocell and multiple small cell access points (SCAs). The SCAs compete for serving the macrocell base station (MBS) users (MUs). The corresponding user association problem is solved by the proposed bid-wait auction (BWA) method. We considered two scenarios. In the first scenario, the MBS initially admits the largest possible set of MUs that it can serve simultaneously and then auctions off the remaining MUs to the SCAs, who are willing to admit guest users (GUs) in addition to their commitments to serve their own host users (HUs). This problem is solved by the proposed forward bid-wait auction (FBWA). In the second scenario, the MBS aims to offload as many MUs as possible to the SCAs and then admits the largest possible set of remaining MUs. This is solved by the proposed backward bid-wait auction (BBWA). The proposed algorithms provide close to optimum solution as if obtained using a centralised global optimization

Network capacity enhancement in HetNets using incentivized offloading mechanism

This work investigates distributed algorithms for joint power allocation and user association in heterogeneous networks. We propose auction-based algorithms for offloading macrocell users (MUs) from the macrocell base station (MBS) to privately owned small-cell access points (SCAs). We first propose a simultaneous multiple-round ascending auction (SMRA) for allocating MUs to SCAs. Taking into account the overheads incurred by SCAs during valuation in the SMRA, further improvements are proposed using techniques known as sub-optimal altered SMRA (ASMRA), the combinatorial auction with item bidding (CAIB) and its variations; the sequential CAIB (SCAIB) and the repetitive CAIB (RCAIB). The proof for existence of the Walrasian equilibrium (WE) is demonstrated through establishing that the valuation function used by the SCAs is a gross substitute. Finally, we show that truthful bidding is individual rational for all of our proposed algorithms

Blockchain-based distributive auction for relay-assisted secure communications

Physical layer security (PLS) is considered as a promising technique to prevent information eavesdropping in wireless systems. In this context, cooperative relaying has emerged as a robust solution for achieving PLS due to multipath diversity and relatively lower transmission power. However, relays or the relay operators in the practical environment are unwilling for service provisioning unless they are incentivized for their cost of services. Thus, it is required to jointly consider network economics and relay cooperation to improve system efficiency. In this paper, we consider the problem of joint network economics and PLS using cooperative relaying and jamming. Based on the double auction theory, we model the interaction between transmitters seeking for a particular level of secure transmission of information and relay operators for suitable relay and jammer assignment, in a multiple source-destination networks. In addition, theoretical analyses are presented to justify that the proposed auction mechanism satisfies the desirable economic properties of individual rationality, budget balance, and truthfulness. As the participants in the traditional centralized auction framework may take selfish actions or collude with each other, we propose a decentralized and trustless auction framework based on blockchain technology. In particular, we exploit the smart contract feature of blockchain to construct a completely autonomous framework, where all the participants are financially enforced by smart contract terms. The security properties of the proposed framework are also discussed

Coordinated multicell beamforming with local and global data rate constraints

© 2016 IEEE.We propose optimization techniques for coordinated multi-cell beamforming in the presence of local users and a global user. The local users are served by only the corresponding basestation (BS) while the global user is served by multiple basestations. The global user, with the aid of multiple antennas, is able to decode multiple data streams transmitted by various transmitters through singular value decomposition of the channels at the receiver and using left dominant singular vectors as the receiver beamforming. The coordinating basestations employ semidefinite programing based transmitter beamforming and agree to perform optimum data rate split for the global user in order to minimise the transmission power

Coordinated multicell beamforming with local and global data rate constraints

© 2016 IEEE.We propose optimization techniques for coordinated multi-cell beamforming in the presence of local users and a global user. The local users are served by only the corresponding basestation (BS) while the global user is served by multiple basestations. The global user, with the aid of multiple antennas, is able to decode multiple data streams transmitted by various transmitters through singular value decomposition of the channels at the receiver and using left dominant singular vectors as the receiver beamforming. The coordinating basestations employ semidefinite programing based transmitter beamforming and agree to perform optimum data rate split for the global user in order to minimise the transmission power

Game-theoretic beamforming techniques for multiuser multi-cell networks under mixed QoS constraints

We propose a game-theoretic approach for the downlink beamformer design for a multiuser multi-cell wireless network under a mixed quality of services criterion. The network has real time users that must attain a specific set of signal-to-interference-plus-noise ratios, and non-real time users whose signal-to-interference-plus-noise ratios should be balanced and maximized. We propose a mixed QoS strategic noncooperative game wherein base stations determine their downlink beamformers in a fully distributed manner. In the case of infeasibility, we have proposed a fall back mechanism which converts the problem to a pure max-min optimization. We further propose the mixed QoS bargain game to improve the Nash equilibrium operating point through Egalitarian and Kalai-Smorodinsky bargaining solutions. We have shown that the results of bargaining games are comparable to that of the optimal solutions