Jasper Goseling

Capacity and Examples of Template-Protecting Biometric Authentication Systems

In this paper, we formulate precisely the requirements for privacy protecting biometric authentication systems. The secrecy capacity Cs is investigated for the discrete and the continuous case. We present, furthermore, a general algorithm that meets the requirements and achieves Cs as well as Cid (the identification capacity). Finally, we present some practical constructions of the general algorithm and analyze their properties.

On the capacity of a biometrical identification system

We investigate fundamental properties of biometrical identification systems. We focus on the capacity, i.e. a measure for the number of individuals that can be reliably identified. It can be expressed using standard information-theoretical concepts.

On Optimal Geographical Caching in Heterogeneous Cellular Networks

In this work we investigate optimal geographical caching in heterogeneous cellular networks where different types of base stations (BSs) have different cache capacities. Users request files from a content library according to a known probability distribution. The performance metric is the total hit probability, which is the probability that a user at an arbitrary location in the plane will find the content that it requires in one of the BSs that it is covered by. We consider the problem of optimally placing content in all BSs jointly. As this problem is not convex, we provide a heuristic scheme by finding the optimal placement policy for one type of base station conditioned on the placement in all other types. We demonstrate that these individual optimization problems are convex and we provide an analytical solution. As an illustration, we find the optimal placement policy of the small base stations (SBSs) depending on the placement policy of the macro base stations (MBSs). We show how the hit probability evolves as the deployment density of the SBSs varies. We show that the heuristic of placing the most popular content in the MBSs is almost optimal after deploying the SBSs with optimal placement policies. Also, for the SBSs no such heuristic can be used; the optimal placement is significantly better than storing the most popular content. Finally, we show that solving the individual problems to find the optimal placement policies for different types of BSs iteratively, namely repeatedly updating the placement policies, does not improve the performance.

Lower bounds on the maximum energy benefit of network coding for wireless multiple unicast

We consider the energy savings that can be obtained by employing network coding instead of plain routing in wireless multiple unicast problems. We establish lower bounds on the benefit of network coding, defined as the maximum of the ratio of the minimum energy required by routing and network coding solutions, where the maximum is over all configurations. It is shown that if coding and routing solutions are using the same transmission range, the benefit in d-dimensional networks is at least . Moreover, it is shown that if the transmission range can be optimized for routing and coding individually, the benefit in 2-dimensional networks is at least 3. Our results imply that codes following a decode-and-recombine strategy are not always optimal regarding energy efficiency.

Distributed storage in the plane

We consider storage devices located in the plane according to a general point process and specialize the results for the homogeneous Poisson process. A large data file is stored at the storage devices, which have limited storage capabilities. Hence, they can only store parts of the data. Clients can contact the storage devices to retrieve the data. We compare the expected cost of obtaining the complete data under uncoded as well as coded data allocation strategies. It is shown that for the general class of cost measures where the cost of retrieving data is increasing with the distance between client and storage devices, coded allocation outperforms uncoded allocation. The improvement offered by coding is quantified for two more specific classes of performance measures. Finally, our results are validated by computing the costs of the allocation strategies for the case that storage devices coincide with currently deployed mobile base stations.

Physical-layer network coding on the random-access channel

We consider a physical-layer network coding strategy for the random-access channel, based on compute-and-forward. When packets collide, it is possible to reliably recover a linear combination of the packets at the receiver. Over many rounds of transmission, the receiver can thus obtain many linear combinations and eventually recover all original packets. This is by contrast to slotted ALOHA where packet collisions lead to complete erasures. In previous work we introduced a compute-and-forward strategy for the two-user random-access channel. In the current work we consider an arbitrary number of users. The strategy is shown to be significantly superior to the best known strategies, including multipacket reception.

Random Access With Physical-Layer Network Coding

We consider a physical-layer network coding strategy for the random-access channel, based on compute-and-forward. When packets collide, it is possible to reliably recover a linear combination of the packets at the receiver. Over many rounds of transmission, the receiver can thus obtain many linear combinations and eventually recover all original packets. This is by contrast to slotted ALOHA where packet collisions lead to complete erasures. The strategy is shown to be significantly superior to the best known strategies, including multipacket reception.

Energy consumption in coded queues for wireless information exchange

We show the close relation between network coding and queuing networks with negative and positive customers. Moreover, we develop Markov reward error bounding techniques for networks with negative and positive customers. We obtain bounds on the energy consumption in a wireless information exchange setting using network coding.

Line and Lattice Networks Under Deterministic Interference Models

Capacity bounds are compared for four different deterministic models of wireless networks, representing four different ways of handling broadcast and superposition in the physical layer. In particular, the transport capacity under a multiple unicast traffic pattern is studied for a 1-D network of regularly spaced nodes on a line and for a 2-D network of nodes placed on a hexagonal lattice. The considered deterministic models are: (i) P/P, a model with exclusive transmission and reception, (ii) P/M, a model with simultaneous reception of the sum of the signals transmitted by all nearby nodes, (iii) B/P, a model with simultaneous transmission to all nearby nodes but exclusive reception, and (iv) B/M, a model with both simultaneous transmission and simultaneous reception. All four deterministic models are considered under half-duplex constraints. For the 1-D scenario, it is found that the transport capacity under B/M is twice that under P/P. For the 2-D scenario, it is found that the transport capacity under B/M is at least 2.5 times, and no more than six times, the transport capacity under P/P. The transport capacities under P/M and B/P fall between these bounds.

Random access with physical-layer network coding

Leveraging recent progress in compute-and-forward we propose an approach to random access that is based on physical-layer network coding: When packets collide, it is possible to recover a linear combination of the packets at the receiver. Over many rounds of transmission, the receiver can thus obtain many linear combinations and eventually recover all original packets. This is by contrast to slotted ALOHA where packet collisions lead to complete erasures. The throughput of the proposed strategy is derived for a system with two users and shown to be significantly superior to the best known strategies, including multipacket reception.