Mireille Sarkiss

Construction of New Delay-Tolerant Space-Time Codes

Perfect space-time codes (STC) are optimal codes in their original construction for multiple-input multiple-output (MIMO) systems. Based on cyclic division algebras (CDA), they are full-rate, full-diversity codes, have non-vanishing determinants (NVD) and hence achieve diversity-multiplexing tradeoff (DMT). In addition, these codes have led to optimal distributed space-time codes when applied in cooperative networks under the assumption of perfect synchronization between relays. However, they lose their diversity when delays are introduced and thus are not delay-tolerant. In this paper, using the cyclic division algebras of perfect codes, we construct new codes that maintain the same properties as perfect codes in the synchronous case. Moreover, these codes preserve their full-diversity in asynchronous transmission.

2 × 2 delay-tolerant distributed space-time codes with non-vanishing determinants

Distributed space-time codes over two asynchronous relays are considered. First, we show that the space-time code proposed in [1] is suitable for asynchronous transmission over two relays. Using tools from division algebra, we study the quadratic form resulting from its determinant and we prove that this code has a non-vanishing determinant over all constellations carved from Zopf[i], and thus is optimal in the sense of diversity-multiplexing tradeoff [2]. Then, we propose a delay-tolerant code based on the Golden code [3] the full-rate full-diversity information lossless space-time code proposed for the MIMO channel, and we deduce the convenient unitary matrices to obtain the modified code. Applying these matrices to other MIMO codes, namely Tirkkonen-Hottinen [4] and Sezginer-Sari code [5], we infer new delay-tolerant codes. In addition of being suitable for asynchronous relay transmission, all the new codes have the same determinants as the old ones.

Joint resource allocation and offloading strategies in cloud enabled cellular networks

The numerous features installed in recent mobile phones opened the door to a wide range of applications involving localization, storage, photo and video taking and communication. A significant number of applications involve user generated content and require intensive processing which limits dramatically the battery lifetime of featured mobile terminals. Mobile cloud computing has been recently proposed as a promising solution allowing the mobile users to run computing-intensive and energy parsimonious applications. This new feature requires new functionalities inside the cellular network architecture and needs appropriate resource allocation strategies which account for computation and communication in the same time. In this paper we present promising options to upgrade 4G architecture to support these new features. We also present two resource allocation strategies accounting for both computation and radio resources. These strategies are devised so that to minimize the energy consumption of the mobile terminals while satisfying predefined delay constraints. We compare online learning based solutions where the network adapts dynamically to the application that is run on mobile terminals, and pre-calculated offline solutions which are employed when a certain level of knowledge about the application and the channel conditions is available at the network side. We show, that even with imperfect knowledge about the application, pre-calculated offline strategies offer better performance in terms of energy consumption of mobile terminals.

Energy-optimal resource scheduling and computation offloading in small cell networks

This paper provides a joint optimization framework of radio resource scheduling and computation offloading in small cell LTE based networks. We consider that mobile users are served by nearby small cell base stations which can be endowed with some computational capabilities. The objective is to minimize the average energy consumption at the user terminal to run its mobile applications, either locally or remotely, while satisfying average delay constraints tolerated by these applications. For this problem, we investigate offline dynamic programming approaches and we devise two solutions: deterministic and randomized, to find the optimal radio scheduling-offloading policy. We show that the dynamic offline strategies are able of achieving optimal energy efficiency at the mobile terminals. Indeed, they can adapt the processing decisions between: local processing, offloading, and staying idle, by exploiting their knowledge on the channel conditions and the application properties.

Secure Joint Cache-Channel Coding over Erasure Broadcast Channels

We derive upper and lower bounds on the secure capacity-memory tradeoff of the two-user wiretap erasure BC with cache memory at the weaker receiver. The bounds coincide when the cache memory exceeds a given threshold. The lower bound also exhibits that cache memories provide larger gains under a secrecy constraint than without such a constraint. Moreover, for a large set of parameters the capacity-memory tradeoff is larger if only the weaker receiver has cache memory than when this cache memory is split equally among the receivers. The lower bound is based on a joint cache-channel coding scheme that simultaneously exploits the cache contents and the channel statistics. Such a joint design yields significant gains over a separation-based design.

Joint multi-user resource scheduling and computation offloading in small cell networks

In this paper, we address computation offloading problem from mobile users to their serving small cell base stations. These base stations can be endowed with some computational capabilities providing thus users proximity access to the cloud services. We aim to jointly optimize the radio resource scheduling and computation offloading in order to minimize the average energy consumed by all the users terminals to process their mobile applications under average delay constraints tolerated by these applications. We investigate for this problem offline and online dynamic programming approaches and we devise deterministic solutions to find the optimal scheduling-offloading policy. The proposed solutions select only one user for scheduling, hence offloading, and decides for the other users either local processing or staying idle according to their application rates. We show that the offline strategy is optimal in terms of energy saving compared to the online strategy. It can benefit from prior knowledge on the channel statistics and the application properties to satisfy the users requirements.

4 × 4 Perfect space-time code partition

In this paper, we partition the 4 times 4 perfect code in order to increase the minimum determinant between codewords, and hence improve the performance in slow fading channels. Using construction A at the encoder, we construct the lattices corresponding to perfect code subcodes at different levels of the partition chain, and we find the convenient binary codes. This partition is made in the same manner as for golden code. We propose also a new decoder, based on stack decoder, which is valid for partitioning schemes. It achieves ML performance with significantly reduced complexity. Suboptimal versions are presented to reduce furthermore the complexity.

Achieving joint secrecy with cache-channel coding over erasure broadcast channels

We derive upper and lower bounds on the secure capacity-memory tradeoff of the K-user (K > 2) wiretap erasure broadcast channel where Kw receivers are weak and have cache memories of equal size, and Ks receivers are strong and have no cache. The bounds coincide for small and large cache memories. The lower bound also exhibits that cache memories provide larger gains under a secrecy constraint than without such a constraint. The lower bound is based on a joint cache-channel coding scheme that simultaneously exploits the cache contents and the channel statistics. Moreover, we show for the two-user scenario that in the regime of small cache memories, the capacity-memory tradeoff is larger when only the weaker receiver has cache memory than when this cache memory is split equally among the two receivers.

Spatial coupling for distributed storage and diversity applications

Low-density parity-check codes are considered for erasure channels, mainly Root-LDPC codes that include a special type of checknodes. Spatial coupling is applied on parity bits of a Root-LDPC ensemble designed for a channel with 4 block-erasure states and a maximal design rate of 3/4 attaining double diversity. The advantage of spatial coupling is shown in the erasure plane as an improvement of a threshold boundary, under independent erasures. The spatial coupling maintains the double diversity because it connects parity bits only. The drawback of this partial coupling is a weak saturation of the threshold boundary towards the capacity boundary.

On the energy efficiency of base station cooperation under limited backhaul capacity

Recently, energy-efficient (EE) communications have received increasing interest specially in cellular networks. Promising techniques, such as multiple input multiple output (MIMO) and base station (BS) cooperation schemes, have been widely studied in the past to improve the spectral efficiency and the reliability. Nowadays, the purpose is to investigate how these techniques can reduce the energy consumption of the systems. In this paper, we address for a single-user scenario, the energy efficiency of two BSs cooperation under limited backhaul capacity. In order to evaluate the EE metric, we provide first an information-theoretical analysis based on the outage probability, for a quantization model over the backhaul. Then, we extend this EE analysis to a more practical approach with data transmission over the backhaul. For both approaches, we identify by numerical/simulation results the cooperation scenarios that can save energy depending on the backhaul capacity.