Stochastic geometry based network interference analysis and control

Abstract

The recent evolution of mobile devices such as tablets and smart-phones has dramatically increased the demands on wireless multi-media services and causes significant interference between communication links in the wireless networks. The network interferences are dynamically changed according to the network geometry such as the locations and the number of nodes and they severely degrade the performance of the network. Recently, the randomness of the networks has been more grown with the newly emerging unplanned or decentralized networks such as small cells and device-to-device (D2D). In addition, the uncertainty for the locations and channels of all nodes in the network has been grown due to the difficulty of predicting all explosively increased communication nodes. Accordingly, understanding and controlling the network interferences of the wireless random networks have become more important. Motivated by this, this dissertation analyzes the network interferences of four different wireless random networks by using stochastic geometry and proposes the network interference control schemes to maximize the performance of each network.

Firstly, the interference control scheme via artificial noise to enhance the physical layer security is proposed in stochastic wireless secrecy network where a transmitter transmits the secret message with artificial noise to the receiver and multiple interferers and eavesdroppers are randomly located. The tradeoff between connection and secrecy outage probabilities with respect to the use of artificial noise is discovered. We derive the secrecy transmission rate and investigate the relationship between artificial noise and various system parameters like secrecy protected zone radius and intensity of interferers and eavesdroppers on the secrecy transmission rate. In interference-limited networks, we derive the optimal power allocation between the information-bearing signal and artificial noise to maximize the achievable secrecy transmission rate subject to maximum allowable connection and secrecy outage probabilities. Numerical results show that artificial noise is still beneficial in the presence of inherent network interference to improve secrecy transmission rate and provide rules of thumb to quantify when optimal power allocation is useful.

Secondly, the interference control scheme via user RAT access control is proposed in multi-RAT cellular networks. From the perspective of a single user, concurrent utilization of all available radio access technologies (RAT) is always beneficial for increasing individual data rate. However, given the interactions among users, occupying multiple RATs at each user might not be optimal from a network-wide viewpoint. In this chapter, we explore the answer to the posed question what is the optimal access strategy in multi-RAT cellular networks, solving a distributed RAT access control problem for maximizing network throughput. With stochastic geometry, we analytically evaluate network throughputs for two different access modes: single RAT access (altruistic access) and simultaneous multiple RATs access (selfish access). Comparing the network throughputs for the two modes, we first show that the network throughput can be maximized by properly mixing the two access modes and then derive the optimal portions of each mode in a network, which motivates a distributed RAT access control in a probabilistic sense. The optimal mixture of the two modes controls scheduling contention and interference among users to maximize the network throughput. We also analyze the effects of various system parameters, such as the number of frequency sub-bands for each RAT, user density, and access point density, on the optimal portions of the two access modes.

Thirdly, the interference control scheme via caching placement is proposed in stochastic wireless caching helper networks. The file transmission success of the wireless caching helpers is determined by the channel selection diversity gain and network interference, where they are dynamically changed according to which files are stored at finite cache of each caching helper for given channel fading and network geometry. This chapter studied the optimal caching placement of the stochastic wireless caching helpers for general cache memory size under Nakagami fading. We proved that finding optimal/sub-optimal caching placement to maximize the average file transmission success probability in noise/interference-limited network is the conventional convex optimization problem and derived the structure of the optimal caching placement in closed-form. It was shown that the optimal caching placement maximizes the average file transmission success probability by optimally balancing the channel selection diversity gain for each file and controlling the network interference for given file popularity and limited cache memory size. Finally, with some numerical examples, we investigated how the various system parameters such as file popularity, caching helper density, Nakagami fading parameter m, pathloss exponent, transmit power, cache memory size, and target file bit rates affect on the optimal caching placement.

Fourthly, the interference control scheme via caching placement is proposed in cooperative wireless caching helper networks. This chapter models the cooperative transmission via caching helpers (cache-based joint transmission), which cache one of the K most popular files, in wireless caching helper networks and analyzes its performance in terms of the file transmission success probability in the stochastic geometry framework. For given caching placement, the caching helpers can either provide a file diversity gain by serving different files or a cooperative gain by jointly transmitting the same files. In order to account for the tradeoff between the file diversity gain and the cooperative gain, the cache hit probability and the rate coverage probability were derived. We also find the optimal caching placement balancing the tradeoff and investigate the effects of various system parameters, such as the cooperative region, the density of caching helpers, and the file popularity exponent, on the optimal caching placement.