In this work, the peak rate of the caching problem is investigated, under the scenario that the users are with small buffer sizes and the number of users is no less than the amount of files in the server. A novel coded caching strategy is proposed for such a scenario, leading to a lower peak rate compared to recent results in the literature. Furthermore, it is verified that our peak rates coincides with the cut-set bound analytically in an information-theoretic view.

This paper investigates the simultaneous wireless information and energy transfer for the non-regenerative multipleinput multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) relaying system. By considering two practical receiver architectures, we present two protocols, time switchingbased relaying (TSR) and power splitting-based relaying (PSR). To explore the system performance limit, we formulate two optimization problems to maximize the end-to-end achievable information rate with the full channel state information (CSI) assumption. Since both problems are non-convex and have no known solution method, we firstly derive some explicit results by theoretical analysis and then design effective algorithms for them. Numerical results show that the performances of both protocols are greatly affected by the relay position. Specifically, PSR and TSR show very different behaviors to the variation of relay position. The achievable information rate of PSR monotonically decreases when the relay moves from the source towards the destination, but for TSR, the performance is relatively worse when the relay is placed in the middle of the source and the destination. This is the first time to observe such a phenomenon. In addition, it is also shown that PSR always outperforms TSR in such a MIMO-OFDM relaying system. Moreover, the effect of the number of antennas and the number of subcarriers are also discussed. Index Terms-Energy harvesting, wireless power transfer, MIMO-OFDM, non-regenerative relaying

Abstract-Millimeter wave provides a very promising approach for meeting the ever-growing traffic demand in next generation wireless networks. To utilize this band, it is crucial to obtain the channel state information in order to perform beamforming and combining to compensate for severe path loss. In contrast to lower frequencies, a typical millimeter wave channel consists of a few dominant paths. Thus it is generally sufficient to estimate the path gains, angles of departure (AoDs), and angles of arrival (AoAs) of those paths. Proposed in this paper is a dual timescale model to characterize abrupt channel changes (e.g., blockage) and slow variations of AoDs and AoAs. This work focuses on tracking the slow variations and detecting abrupt changes. A Kalman filter based tracking algorithm and an abrupt change detection method are proposed. The tracking algorithm is compared with the adaptive algorithm due to Alkhateeb, Ayach, Leus and Heath (2014) in the case with single radio frequency chain. Simulation results show that to achieve the same tracking performance, the proposed algorithm requires much lower signal-to-noise-ratio (SNR) and much fewer pilots than the other algorithm. Moreover, the change detection method can always detect abrupt changes with moderate number of pilots and SNR.

This paper investigates the UAV-enabled wireless powered cooperative mobile edge computing (MEC) system, where a UAV installed with an energy transmitter (ET) and an MEC server provides both energy and computing services to sensor devices (SDs). The active SDs desire to complete their computing tasks with the assistance of the UAV and their neighboring idle SDs that have no computing task. An optimization problem is formulated to minimize the total required energy of UAV by jointly optimizing the CPU frequencies, the offloading amount, the transmit power and the UAV's trajectory. To tackle the non-convex problem, a successive convex approximation (SCA)based algorithm is designed. Since it may be with relatively high computational complexity, as an alternative, a decomposition and iteration (DAI)-based algorithm is also proposed. Simulation results show that both proposed algorithms converge within several iterations, and the DAI-based algorithm achieves the similar minimal required energy and optimized trajectory with the SCA-based one. Moreover, for a relatively large amount of data, the SCA-based algorithm should be adopted to find an optimal solution, while for a relatively small amount of data, the DAI-based algorithm is a better choice to achieve the smaller computing energy consumption. It also shows that the trajectory optimization plays a dominant factor in minimizing the total required energy of the system and optimizing acceleration has a great effect on the required energy of the UAV. Additionally, by jointly optimizing the UAV's CPU frequencies and the amount of bits offloaded to UAV, the minimal required energy for computing can be greatly reduced compared to other schemes. And, by leveraging the computing resources of idle SDs, the UAV's computing energy can also be greatly reduced.

Energy harvesting technique is a potential way for relay node energy supply in cooperative networks in the respect of deployment flexibility and maintenance charge reduction. However, unlike traditional power source, it is intuitive that the fluctuation of harvested energy flow can degrade the benefit resulted from relay-aided cooperative transmission. To this end, this paper focuses on the performance analysis of energy harvesting relay-aided cooperative network under slow fading channel from a perspective of outage behavior, and attempts to derive the closed-form expression of outage probability of the proposed cooperative protocol. Compared with simple direct transmission protocol, it is proved that a multiplicative gain for improving system performance in terms of minimizing outage probability can be obtained by energy harvesting relay-aided cooperative transmission. In particular, if there are multiple available relay nodes around the environment or the energyexhausted probability of relay node is small, it is very profitable to employ relay-aided cooperative transmission protocol.

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This paper investigates the energy efficiency (EE) in multiple relay aided OFDM system, where decode-and-forward (DF) relay beamforming is employed to help the information transmission. In order to explore the EE performance with user fairness for such a system, we formulate an optimization problem to maximize the EE by jointly considering several factors, the transmission mode selection (DF relay beamforming or direct-link transmission), the helping relay set selection, the subcarrier assignment and the power allocation at the source and relays on subcarriers, under nonlinear proportional rate fairness constraints, where both transmit power consumption and linearly rate-dependent circuit power consumption are taken into account. To solve the non-convex optimization problem, we propose a low-complexity scheme to approximate it. Simulation results demonstrate its effectiveness. We also investigate the effects of the circuit power consumption on system performances and observe that with both the constant and the linearly rate-dependent circuit power consumption, system EE grows with the increment of system average channel-to noise ratio (CNR), but the growth rates show different behaviors. For the constant circuit power consumption, system EE increasing rate is an increasing function of the system average CNR, while for the linearly rate-dependent one, system EE increasing rate is a decreasing function of the system average CNR. This observation is very important which indicates that by deducing the circuit dynamic power consumption per unit data rate, system EE can be greatly enhanced. Besides, we also discuss the effects of the number of users and subcarriers on the system EE performance.

This paper investigates the simultaneous wireless information and power transfer (SWIPT) in cooperative relay networks, where a relay harvests energy from the radio frequency (RF) signals transmitted by a source and then uses the harvested energy to assist the information transmission from the source to its destination. Both source and relay transmissions use rateless code, which allows the destination to employ any of the two information receiving strategies, i.e., the mutual information accumulation (IA) and the energy accumulation (EA). The SWIPT-enabled relay employs three different SWIPT receiver architectures, the ideal receiver and two practical receivers (i.e., the power splitting (PS) and the time switch (TS) receivers). Accordingly, three relaying protocols, namely, ideal protocol, PS protocol and TS protocol, are presented. In order to explore the system performance limits with these three protocols, optimization problems are formulated to maximize their achievable information rates.For the ideal protocol, explicit expressions of the optimal solutions are derived. For the PS protocol, a linear-search algorithm is designed to solve the non-convex problems. For the TS protocol, two solving methods are presented. Numerical experiments are carried out to validate our analysis and algorithms, which also show that, with the same SWIPT receiver, the IA-based system outperforms the EA-based system, while with the same information receiving strategy, PS protocol outperforms DRAFT 2 TS protocol. Moreover, compared with conventional non-SWIPT and non-rateless-coded systems, the proposed protocols exhibit considerable performance gains, especially in relatively low signal-to-noise ratio (SNR) regime. Besides, the effects of the source-destination direct link and the relay position on system performance are also discussed, which provides insights on SWIPT-enabled relay systems. Index TermsEnergy harvesting, wireless information and power transfer, cooperative relaying, rateless codes. I. INTRODUCTIONRecently, integrating energy harvesting (EH) technologies into communication networks has attracted much attention [1]-[6], as it provides an effective way to implement green communications and to extend the lifetime of energy-constrained systems, including wireless sensor networks (WSN) and wireless body area networks (WBAN), etc. In EH-enabled communication networks, EH nodes can harvest energy from surrounding environment to power their operations.Apart from the conventional energy sources, e.g., solar, wind and thermoelectric energy, etc, [1]- [3], energy can also be harvested from radio frequency (RF) signals transmitted from other nodes with fixed energy supply such as power gird or high capacity batteries [4]. In [5], it was pointed out that information and energy can be simultaneously received from the RF signals as both energy and information are carried in transmitted RF signals, referred to as simultaneous wireless information and power transfer (SWIPT) [5]- [6]. Compared with conventional EH methods, SWIPT i...