Interference networks with caches at both ends

This paper studies the fundamental tradeoff between storage and latency in a general wireless interference network with caches equipped at all transmitters and receivers. The tradeoff is characterized by an information-theoretic metric, \emph{normalized delivery time} (NDT), which is the worst-case delivery time of the actual traffic load at a transmission rate specified by degrees of freedom (DoF) of a given channel. We obtain both an achievable upper bound and a theoretical lower bound of the minimum NDT for any number of transmitters, any number of receivers, and any feasible cache size tuple. We show that the achievable NDT is exactly optimal in certain cache size regions, and is within a bounded multiplicative gap to the theoretical lower bound in other regions. In the achievability analysis, we first propose a novel cooperative transmitter/receiver coded caching strategy. It offers the freedom to adjust file splitting ratios for NDT minimization. We then propose a delivery strategy which transforms the considered interference network into a new class of cooperative X-multicast channels. It leverages local caching gain, coded multicasting gain, and transmitter cooperation gain (via interference alignment and interference neutralization) opportunistically. Finally, the achievable NDT is obtained by solving a linear programming problem. This study reveals that with caching at both transmitter and receiver sides, the network can benefit simultaneously from traffic load reduction and transmission rate enhancement, thereby effectively reducing the content delivery latency.

Caching is an effective technique to improve user perceived experience for content delivery in wireless networks. Wireless caching differs from traditional web caching in that it can exploit the broadcast nature of wireless medium and hence, opportunistically change the network topologies. This paper studies a cache-aided MIMO interference network with three transmitters each equipped with M antennas and three receivers each with N antennas. With caching at both the transmitter and receiver sides, the network is changed to hybrid forms of MIMO broadcast channel, MIMO X channel, and MIMO multicast channels. We analyze the degrees of freedom (DoF) of these new channel models using practical interference management schemes. Based on the collective use of these DoF results, we then obtain an achievable normalized delivery time (NDT) of the network, an information-theoretic metric that evaluates the worst-case delivery time at given cache sizes. The obtained NDT is for arbitrary M, N, and any feasible cache sizes. It is shown to be optimal in certain cases and within a multiplicative gap of 3 from the optimum in other cases. The extension to the network with arbitrary number of transmitters and receivers is also discussed.

This paper studies the Multi-Input-Multi-Output (MIMO) interference networks with arbitrary number of transmitters and receivers, where both the transmitters and receivers are equipped with caches. Our objective is to propose content placement and delivery schemes that minimize the worst case normalized delivery time (NDT). First, we design a delivery scheme for the cache-aided Single-Input-Multiple-Output (SIMO) interference networks. Then, we obtain the achievable NDT of the cache-aided MIMO interference networks by using the decomposition property. The numerical results show the superiority of our proposed scheme over the state-of-the-art schemes in the literature. Furthermore, we show that increasing the receiver-cache sizes achieves a higher gain than increasing the number of receive-antennas. In other words, the coded caching gain has a more significant contribution in reducing the transmission latency than the spatial multiplexing gain.

This letter investigates the caching and delivery strategies in a multiple-input multiple-output (MIMO) fog radio access network (Fog-RAN). We focus on the small cache size scenario where the accumulated cache memories of all edge nodes (ENs) are not enough to cache the whole database. We propose a new file splitting and placement scheme tailored for the small cache size, which offers the freedom to adjust the duplication order of the cached contents to minimize the normalized delivery time (NDT). In the fronthaul delivery, we use multiple antennas to multiplex multiple messages while in the access delivery, transmitter cooperation induced by the duplicated contents among ENs is utilized to cancel interference. By jointly optimizing caching and delivery, we obtain an achievable minimum NDT. It is shown that the achievable NDT is within an additive gap of 1 to the theoretical optimum.

The throughput of existing MIMO LANs is limited by the number of antennas on the AP. This paper shows how to overcome this limit. It presents interference alignment and cancellation (IAC), a new approach for decoding concurrent sender-receiver pairs in MIMO networks. IAC synthesizes two signal processing techniques, interference alignment and interference cancellation, showing that the combination applies to scenarios where neither interference alignment nor cancellation applies alone. We show analytically that IAC almost doubles the throughput of MIMO LANs. We also implement IAC in GNU-Radio, and experimentally demonstrate that for 2x2 MIMO LANs, IAC increases the average throughput by 1.5x on the downlink and 2x on the uplink.

For interference alignment (IA) with no channel extension, determining the existence of IA solution for general system parameters is still an open problem. This same problem also exists in interference alignment and cancellation (IAC), which combines IA with interference cancellation in the receivers, involving a new receiver architecture associated with signaling over backhaul links among them. As IAC is expected to achieve more degrees of freedom (DoF) than IA, the existence of IAC solution would be another interesting, yet challenging issue to investigate. In this paper, we have proposed a specific alignment scheme, which allows for the derivation of closed-form IAC solution. Furthermore, we establish and prove the general necessary and sufficient condition to determine the existence of closed-form IAC solution for a Gaussian interference multiple access channel (MAC) with K receivers and J users, each with M antennas.

Recent demand for capacity increase in mobile communications urges the development of both multiple- input multiple-output (MIMO) and small cells. However, overlapping coverage areas between neighboring small cells results in interference-limited networks, where the capacity of the network is severely degraded without superior intercell interference management (IIM) techniques. As one of the superior IIM techniques, the power control intercell interference coordination (ICIC) optimizes downlink transmit powers in the network. This paper proposes an IIM scheme consisting of both neural networks (NNs) power control on the transmitter side and interference cancellation (IC) on the receiver side. Computer simulations examine networks of MIMO systems with the power optimization using some ICIC algorithms: NN, the greedy search, the belief propagation (BP), and the maximum power, combined with IC on the receiver side. In addition, the deep learning, a breakthrough technique for NN with multi-layer structures, is also applied to mobile communications. The results show that the performance of NN is very close to that of the greedy search and superior to that of BP. Complexity of NN is much less than that of BP, and thus NN is suitable for IIM. It is also demonstrated that employing IC provides high capacity gain.

Interference channel, in which multiple user pairs communicate over shared resources, is a building block of communications networks. Here, the K-user interference channel (IC) aided by J instantaneous relays (IRs), i.e. relays without delay, is considered. For KICJR networks, where K>2 and J>1, the DoF performance and achievable schemes have not been investigated in literature. Here, we devise a novel achievable scheme, called restricted interference alignment (RIA), which restricts the received interference from each source at each destination in a limited sub-space, and then, aligns the restricted interferences. Furthermore, we develop an analytical tool for finding a tight upper bound on DoF of KICJR networks by analyzing the properness of the interference alignment equations. Moreover, we develop linear beamforming design for sources and relays based on the mean square error (MSE) minimization, as an achievable scheme. The performance evaluation results show that the achievable sum DoF by using the proposed RIA scheme and the MSE-based beamforming design match well with the derived upper bounds. Furthermore, the results confirm that the achieved sum DoF using the RIA scheme outperforms the existing achievable schemes. Motivated by these promising results, we further investigate impact of IRs in providing physical layer security, i.e. achieving secure DoF in interference networks. Specifically, we derive a lower bound on the achievable secure DoF by devising an achievable scheme, called transmission in the null space (TNS). This scheme makes the cross channels rank deficient and enables sources to select their transmit filters in the constructed null spaces. Performance evaluation shows that by leveraging IRs, the secure DoF performance of interference networks could be increased significantly. The proposed analytical framework in this work for rank deficiency-powered DoF analysis is expected to also attract attention from other research areas, e.g. beamforming design for millimeter wave communications.

Abstract: In SISO (single input and single output) system, refers to have only one input and one output. Here only one antenna is used at receiver and transmitter side. SISO are relatively simple to design and implement. They are of low cost and used in wide range of applications. However, SISO systems are poor in performance and deliver low data rate. So we’ll prefer MIMO (multiple input and multiple output) over SISO as it gives better spectral efficiency, improved reliability and good coverage. In MIMO we use multiple antennas at transmitter and receiver side which is known as Spatial Multiplexing(SM) which enhances the data rate. In the paper the performance of spatial combining MIMO system is analysed. Matlab used for simulation.

Many works considered the CSI uncertainty effect on interference alignment (IA) in MIMO narrow-band interference channel (IC). However, much less attention has been paid to CSI uncertainty effect on IA in SISO frequency-selective IC. This is partially due to the impractical requirement of infinitely large number of subcarriers to implement IA in such channel. Recently, a new approach was proposed to alleviate this limitation through applying IA in time domain while utilizing the guard interval [1]. In this paper, we investigate the performance of this approach under CSI imperfection. We also propose robust transceiver design algorithm that maximizes the received SINR accounting for the CSI imperfection in SISO frequency selective IC. In addition, the average sum stream rate under CSI imperfection is derived.

In this contribution, an adaptive underwater acoustic modem with high bandwidth and power efficiency is proposed. Key features include interleave-division multiplexing (IDM) in time and frequency domain (and optionally in the spatial domain) in conjunction with generalized (non-orthogonal) multi-carrier (MC) transmission. IDM is a special form of superposition coded modulation. At the receiver side, joint intersymbol interference (ISI) and adjacent channel interference (ACI) cancellation is performed, in addition to iterative decoding. Adaptation (with respect to variable data rates, variable signal power, variable signal bandwidth, variable range, variable channel conditions, variable service requirements, etc.) is supported to an extend, which is currently unknown in the area of underwater communications. The communication signal can be used for navigation/positioning purposes without modification at the transmitter side. The system design is easily applicable in underwater networks, and extendable to an arbitrary number of transducers (MIMO processing). The modem is implemented by means of software-defined radio. A wide range of potential applications is targeted.

It is very important that the radar sensor network has autonomous capabilities such as self-managing, etc. Quite often, MIMO interference channels are applied to radar sensor networks, and for self-managing purpose, interference management in MIMO interference channels is critical. Interference alignment (IA) has the potential to dramatically improve system throughput by effectively mitigating interference in multi-user networks at high signal-to-noise (SNR). However, the implementation of IA predominantly relays on perfect and global channel state information (CSI) at all transceivers. A large amount of CSI has to be fed back to all transmitters, resulting in a proliferation of feedback bits. Thus, IA with limited feedback has been introduced to reduce the sum feedback overhead. In this paper, by exploiting the advantage of heterogeneous path loss, we first investigate the throughput of IA with limited feedback in interference channels while each user transmits multi-streams simultaneously, then we get the upper bound of sum rate in terms of the transmit power and feedback bits. Moreover, we propose a dynamic feedback scheme via bit allocation to reduce the throughput loss due to limited feedback. Simulation results demonstrate that the dynamic feedback scheme achieves better performance in terms of sum rate.

Fog radio access network (F-RAN) architectures can leverage both cloud processing and edge caching for content delivery to the users. To this end, F-RAN utilizes caches at the edge nodes (ENs) and fronthaul links connecting a cloud processor to ENs. Assuming time-invariant content popularity, existing information-theoretic analyses of content delivery in F-RANs rely on offline caching with separate content placement and delivery phases. In contrast, this paper focuses on the scenario in which the set of popular content is time-varying, hence necessitating the online replenishment of the ENs’ caches along with the delivery of the requested files. The analysis is centered on the characterization of the long-term normalized delivery time (NDT), which captures the temporal dependence of the coding latencies accrued across multiple time slots in the high signal-to-noise ratio regime. Online edge caching and delivery schemes are investigated for both serial and pipelined transmission modes across fronthaul and edge segments. Analytical results demonstrate that, in the presence of a time-varying content popularity, the rate of fronthaul links sets a fundamental limit on the long-term NDT of F-RAN system. Analytical results are further verified by numerical simulation, yielding important design insights.

Interference alignment (IA) is a suggested technique for multiple input multiple output (MIMO) based multipath interference channels to achieve large multiplexed gain. CSI (Channel state information) is required by IA schemes to design precoding vectors at the transmitter side. There will be significant capacity overhead in feedback link. This paper concentrates on the MIMO channels which are having overtime-correlated differential CSI feedback employed by IA design. Utmost multiplexing gain is obtained by the lowest amount of differential feedback. Because of restricted differential feedback, the interference in the upper bound is avoided by using IA system through differential CSI feedback. The analytical performance of the proposed algorithm is done using simulation results and achieved better Sum rate by using normal differential feedback and by using differential feedback through the Lloyd's algorithm.

Interference Alignment in Multi-user MIMO Systems