arXiv subjects

Eleftherios Lampiris

Publications and source records attributed to Eleftherios Lampiris.

10 recordsLinked to original sources

arXiv2025

Collaborative Coded Caching for Partially Connected Networks

Coded caching leverages the differences in user cache memories to achieve gains that scale with the total cache size, alleviating network congestion due to high-quality content requests. Additionally, distributing transmitters over a wide area can mitigate the adverse effects of path loss. In this work, we consider a partially connected network where the channel between distributed transmitters (helpers) and users is modeled as a distributed multiple-input-multiple-output (MIMO) Gaussian broadcast channel. We propose a novel delivery scheme consisting of two phases: partitioning and transmission. In the partitioning phase, users with identical cache profiles are partitioned into the minimum number of sets, such that users within each set can successfully decode their desired message from a joint transmission enabled by MIMO precoding. To optimally partition the users, we employ the branch and bound method. In the transmission phase, each partition is treated as a single entity, and codewords are multicast to partitions with distinct cache profiles. The proposed delivery scheme is applicable to any partially connected network, and while the partitioning is optimal, the overall delivery scheme, including transmission, is heuristic. Interestingly, simulation results show that its performance closely approximates that of the fully connected optimal solution.

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arXiv2024

Adapt or Wait: Quality Adaptation for Cache-aided Channels

This work focuses on quality adaptation as a means to counter the effects of channel degradation in wireless, cache-aided channels. We design a delivery scheme which combines coded caching, superposition coding, and scalable source coding, while keeping the caching scheme oblivious to channel qualities. By properly adjusting the quality at the degraded users we are able to satisfy all demands in a time-efficient manner. In addition, superposition coding allows us to serve high-rate users with high content quality without subjecting them to a delay penalty caused by users with lower rate channels. We design a communication framework that covers all possible channel rate and quality configurations and we further provide algorithms that can optimise the served quality. An interesting outcome of this work is that a modest quality reduction at the degraded users can counter the effects of significant channel degradation. For example, in a 100-user system with normalized cache size 1/10 at each user, if 10 users experience channel degradation of 60% compared to the rate of the non-degraded users, we show that our transmission strategy leads to a 85% quality at the degraded users and perfect quality at the non-degraded users.

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arXiv2021

Fundamental Limits of Wireless Caching Under Mixed Cacheable and Uncacheable Traffic

We consider cache-aided wireless communication scenarios where each user requests both a file from an a-priori generated cacheable library (referred to as 'content'), and an uncacheable 'non-content' message generated at the start of the wireless transmission session. This scenario is easily found in real-world wireless networks, where the two types of traffic coexist and share limited radio resources. We focus on single-transmitter, single-antenna wireless networks with cache-aided receivers, where the wireless channel is modelled by a degraded Gaussian broadcast channel (GBC). For this setting, we study the delay-rate trade-off, which characterizes the content delivery time and non-content communication rates that can be achieved simultaneously. We propose a scheme based on the separation principle, which isolates the coded caching and multicasting problem from the physical layer transmission problem. We show that this separation-based scheme is sufficient for achieving an information-theoretically order optimal performance, up to a multiplicative factor of 2.01 for the content delivery time, when working in the generalized degrees of freedom (GDoF) limit. We further show that the achievable performance is near-optimal after relaxing the GDoF limit, up to an additional additive factor of 2 bits per dimension for the non-content rates. A key insight emerging from our scheme is that in some scenarios considerable amounts of non-content traffic can be communicated while maintaining the minimum content delivery time, achieved in the absence of non-content messages; compliments of 'topological holes' arising from asymmetries in wireless channel gains.

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arXiv2021

Multi-Transmitter Coded Caching Networks with Transmitter-side Knowledge of File Popularity

This work presents a new way of exploiting non-uniform file popularity in coded caching networks. Focusing on a fully-connected fully-interfering wireless setting with multiple cache-enabled transmitters and receivers, we show how non-uniform file popularity can be used very efficiently to accelerate the impact of transmitter-side data redundancy on receiver-side coded caching. This approach is motivated by the recent discovery that, under any realistic file-size constraint, having content appear in multiple transmitters can in fact dramatically boost the speed-up factor attributed to coded caching. We formulate an optimization problem that exploits file popularity to optimize the placement of files at the transmitters. We then provide a proof that reduces significantly the variable search space, and propose a new search algorithm that solves the problem at hand. We also prove an analytical performance upper bound, which is in fact met by our algorithm in the regime of many receivers. Our work reflects the benefits of allocating higher cache redundancy to more popular files, but also reflects a law of diminishing returns where for example very popular files may in fact benefit from minimum redundancy. In the end, this work reveals that in the context of coded caching, employing multiple transmitters can be a catalyst in fully exploiting file popularity, as it avoids various asymmetry complications that appear when file popularity is used to alter the receiver-side cache placement.

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arXiv2020

Full Coded Caching Gains for Cache-less Users

Within the context of coded caching, the work reveals the interesting connection between having multiple transmitters and having heterogeneity in the cache sizes of the receivers. Our work effectively shows that having multiple transmit antennas -- while providing full multiplexing gains -- can also simultaneously completely remove the performance penalties that are typically associated to cache-size unevenness. Focusing on the multiple-input single-output Broadcast Channel, the work first identifies the performance limits of the extreme case where cache-aided users coincide with users that do not have caches, and then expands the analysis to the case where both user groups are cache-aided but with heterogeneous cache-sizes. In the first case, the main contribution is a new algorithm that employs perfect matchings on a bipartite graph to offer full multiplexing as well as full coded-caching gains to both cache-aided as well as cache-less users. An interesting conclusion is that, starting from a single-stream centralized coded caching setting with normalized cache size $γ$, then adding $L$ antennas allows for the addition of {up to} approximately $L/γ$ extra cache-less users, at no added delay costs. Similarly surprising is the finding that, {beginning} with a single-antenna hybrid system (with both cache-less and cache-aided users), then adding {$L-1$} antennas to the transmitter, as well as endowing the cache-less users with a cumulative normalized cache size $Γ_2$, increases the Degrees of Freedom by a \emph{multiplicative} factor of up to $Γ_{2}+L$.

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arXiv2020

Resolving the Feedback Bottleneck of Multi-Antenna Coded Caching

Multi-antenna cache-aided wireless networks have been known to suffer from a severe feedback bottleneck, where achieving the maximal Degrees-of-Freedom (DoF) performance required feedback from all served users. These costs matched the caching gains and thus scaled with the number of users. In the context of the $L$-antenna MISO broadcast channel with $K$ receivers having normalized cache size $γ$, we pair a fundamentally novel algorithm together with a new information-theoretic converse, and identify the optimal tradeoff between feedback costs and DoF performance, by showing that having CSIT from only $C<L$ served users implies an optimal one-shot linear DoF of $C+Kγ$. As a side consequence of this, we also now understand that the well known DoF performance $L+Kγ$ is in fact exactly optimal. In practice, the above means that we are now able to disentangle caching gains from feedback costs, thus achieving unbounded caching gains at the mere feedback cost of the multiplexing gain. This further solidifies the role of caching in boosting multi-antenna systems; caching now can provide unbounded DoF gains over multi-antenna downlink systems, at no additional feedback costs. The above results are extended to also include the corresponding multiple transmitter scenario with caches at both ends.

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arXiv2020

Fundamental Limits of Wireless Caching under Uneven-Capacity Channels

This work identifies the fundamental limits of cache-aided coded multicasting in the presence of the well-known `worst-user' bottleneck. This stems from the presence of receiving users with uneven channel capacities, which often forces the rate of transmission of each multicasting message to be reduced to that of the slowest user. This bottleneck, which can be detrimental in general wireless broadcast settings, motivates the analysis of coded caching over a standard Single-Input-Single-Output (SISO) Broadcast Channel (BC) with K cache-aided receivers, each with a generally different channel capacity. For this setting, we design a communication algorithm that is based on superposition coding that capitalizes on the realization that the user with the worst channel may not be the real bottleneck of communication. We then proceed to provide a converse that shows the algorithm to be near optimal, identifying the fundamental limits of this setting within a multiplicative factor of 4. Interestingly, the result reveals that, even if several users are experiencing channels with reduced capacity, the system can achieve the same optimal delivery time that would be achievable if all users enjoyed maximal capacity.

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arXiv2019

Wyner's Network on Caches: Combining Receiver Caching with a Flexible Backhaul

In this work, we study a large linear interference network with an equal number of transmitters and receivers, where each transmitter is connected to two subsequent receivers. Each transmitter has individual access to a backhaul link (fetching the equivalent of $M_{T}$ files), while each receiver can cache a fraction $γ$ of the library. We explore the tradeoff between the communication rate, backhaul load, and caching storage by designing algorithms that can harness the benefits of cooperative transmission in partially connected networks, while exploiting the advantages of multicast transmissions attributed to user caching. We show that receiver caching and fetching content from the backhaul are two resources that can simultaneously increase the delivery performance in synergistic ways. Specifically, an interesting outcome of this work is that user caching of a fraction $γ$ of the library can increase the per-user Degrees of Freedom (puDoF) by $γ$. Further, the results reveal significant savings in the backhaul load, even in the small cache size region. For example, the puDoF achieved using the pair $(M_{T}=8, γ=0)$ can also be achieved with the pairs $(M_{T}=4,γ=0.035)$ and $(M_{T}=2,γ=0.1)$, showing that even small caches can provide significant savings in the backhaul load.

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arXiv2018

Coded Distributed Computing with Node Cooperation Substantially Increases Speedup Factors

This work explores a distributed computing setting where $K$ nodes are assigned fractions (subtasks) of a computational task in order to perform the computation in parallel. In this setting, a well-known main bottleneck has been the inter-node communication cost required to parallelize the task, because unlike the computational cost which could keep decreasing as $K$ increases, the communication cost remains approximately constant, thus bounding the total speedup gains associated to having more computing nodes. This bottleneck was substantially ameliorated by the recent introduction of coded MapReduce techniques which allowed each node --- at the computational cost of having to preprocess approximately $t$ times more subtasks --- to reduce its communication cost by approximately $t$ times. In reality though, the associated speed up gains were severely limited by the requirement that larger $t$ and $K$ necessitated that the original task be divided into an extremely large number of subtasks. In this work we show how node cooperation, along with a novel assignment of tasks, can help to dramatically ameliorate this limitation. The result applies to wired as well as wireless distributed computing, and it is based on the idea of having groups of nodes compute identical parallelization (mapping) tasks and then employing a here-proposed novel D2D coded caching algorithm.

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arXiv2018

Adding transmitters dramatically boosts coded-caching gains for finite file sizes

In the context of coded caching in the $K$-user BC, our work reveals the surprising fact that having multiple ($L$) transmitting antennas, dramatically ameliorates the long-standing subpacketization bottleneck of coded caching by reducing the required subpacketization to approximately its $L$th root, thus boosting the actual DoF by a multiplicative factor of up to $L$. In asymptotic terms, this reveals that as long as $L$ scales with the theoretical caching gain, then the full cumulative (multiplexing + full caching) gains are achieved with constant subpacketization. This is the first time, in any known setting, that unbounded caching gains appear under finite file-size constraints. The achieved caching gains here are up to $L$ times higher than any caching gains previously experienced in any single- or multi-antenna fully-connected setting, thus offering a multiplicative mitigation to a subpacketization problem that was previously known to hard-bound caching gains to small constants. The proposed scheme is practical and it works for all values of $K,L$ and all cache sizes. The scheme's gains show in practice: e.g. for $K=100$, when $L=1$ the theoretical caching gain of $G=10$, under the original coded caching algorithm, would have needed subpacketization $S_1 = \binom{K}{G}= \binom{100}{10} > 10^{13}$, while if extra transmitting antennas were added, the subpacketization was previously known to match or exceed $S_1$. Now for $L=5$, our scheme offers the theoretical (unconstrained) cumulative DoF $d_L = L+G = 5+10=15$, with subpacketization $S_L=\binom{K/L}{G/L} =\binom{100/5}{10/5} = 190$. The work extends to the multi-server and cache-aided IC settings, while the scheme's performance, given subpacketization $S_L=\binom{K/L}{G/L}$, is within a factor of 2 from the optimal linear sum-DoF.

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