Seong Lyun Kim

Joint data rate and power allocation for lifetime maximization in interference limited ad hoc networks

In this paper, we consider the following problem in the wireless ad hoc network: Given a set of paths between source and destination, how to divide the data flow among the paths and how to control the transmission rates, times, and powers of the individual links in order to maximize the operation time of the worst network node. If all nodes are of equal importance, the operation time of the worst node is also the lifetime of the network. By solving the problem, our aim is to investigate how the network lifetime is affected by link conditions such as the maximum transmission power of a node and the peak data rate of a link. For the purpose, we start from a system model that incorporates the carrier to interference ratio (CIR) into a variable data rate of a link. With this, we can develop an iterative algorithm for the lifetime maximization, which resembles to the distributed power control in cellular systems. Numerical examples on the iterative algorithm are included to illustrate the network lifetime as a function of the maximum transmission power and the peak data rate.

Adaptive Inter-Cell Interference Management for Downlink FH-OFDMA Systems

For a cellular system, the system throughput as well as the throughput at a cell edge are among the most important evaluation measures for the requirements on the system performance. Several inter-cell interference mitigation techniques have been proposed to meet the cell-edge users needs in downlink. Each interference mitigation scheme has been found that they have pros and cons at the same time. In this paper, an adaptive inter-cell interference management scheme is proposed for an LDPC-coded FH-OFDMA system to combat the inter-cell interference in downlink cellular environment. Based on the knowledge on other cells that we can utilize without dynamic cooperation between cells, different decoding methods can be applied to maximize the performance for the cell-edge users. It is shown that a significant gain can be obtained, especially at the cell boundary using the proposed scheme.

Downlink Resource Management in the Frequency Domain for Multicell OFCDM Wireless Networks

Recently, various versions of combining code division multiple access (CDMA) with orthogonal frequency-division multiplexing (OFDM) have drawn much attention for IMT-advanced (4G) and new broadcasting systems. In particular, variable-spreading-factor orthogonal frequency and code multiplexing (OFCDM) and multicarrier CDMA adopt 2-D spreading, i.e., time-domain and frequency-domain spreading. Maeda , Yang and Hanzo, Zheng , and Zhou have mentioned a few strong points of 2-D spreading. However, what is missing in their analysis/simulations is the system-level aspect of 2-D spreading. In particular, we are interested in the following questions: ldquoWhat are the advantages of frequency-domain spreading in multicell environments?rdquo and ldquoWhat is the optimal frequency reuse factor in 2-D spreading systems?rdquo Answers to these questions are investigated in this correspondence.

Revisiting frequency reuse towards supporting ultra-reliable ubiquitous-rate communication

One of the goals of 5G wireless systems stated by the NGMN alliance is to provide moderate rates (50+ Mbps) everywhere and with very high reliability. We term this service Ultra-Reliable Ubiquitous-Rate Communication (UR2C). This paper investigates the role of frequency reuse in supporting UR2C in the downlink. To this end, two frequency reuse schemes are considered: user-specific frequency reuse (FRu) and BS-specific frequency reuse (FRb). For a given unit frequency channel, FRu reduces the number of serving user equipments (UEs), whereas FRb directly decreases the number of interfering base stations (BSs). This increases the distance from the interfering BSs and the signal-to-interference ratio (SIR) attains ultra-reliability, e.g. 99% SIR coverage at a randomly picked UE. The ultra-reliability is, however, achieved at the cost of the reduced frequency allocation, which may degrade overall downlink rate. To fairly capture this reliability-rate tradeoff, we propose ubiquitous rate defined as the maximum downlink rate whose required SIR can be achieved with ultra-reliability. By using stochastic geometry, we derive closed-form ubiquitous rate as well as the optimal frequency reuse rules for UR2C.

Live Prefetching for Mobile Computation Offloading

Mobile computation offloading refers to techniques for offloading computation intensive tasks from mobile devices to the cloud so as to lengthen the formers’ battery lives and enrich their features. The conventional designs fetch (transfer) user-specific data from mobiles to the cloud prior to computing, called offline prefetching. However, this approach can potentially result in excessive fetching of large volumes of data and cause heavy loads on radio-access networks. To solve this problem, the novel technique of live prefetching, which seamlessly integrates the task-level computation prediction and prefetching within the cloud-computing process of a large program with numerous tasks, is proposed in this paper. The technique avoids excessive fetching but retains the feature of leveraging prediction to reduce the program runtime and mobile transmission energy. By modeling the tasks in an offloaded program as a stochastic sequence, stochastic optimization is applied to design fetching policies to minimize mobile energy consumption under a deadline constraint. The policies enable real-time control of the prefetched-data sizes of candidates for future tasks. For slow fading, the optimal policy is derived and shown to have a threshold-based structure, selecting candidate tasks for prefetching and controlling their prefetched data based on their likelihoods. The result is extended to design close-to-optimal prefetching policies to fast fading channels. Compared with fetching without prediction, live prefetching is shown theoretically to always achieve reduction on mobile energy consumption.

Co-Primary Spectrum Sharing for Inter-Operator Device-to-Device Communication

The business potential of device-to-device (D2D) communication including public safety and vehicular communications will be realized only if direct communication between devices subscribed to different mobile operators (OPs) is supported. One possible way to implement inter-operator D2D communication may use the licensed spectrum of the OPs, i.e., OPs agree to share spectrum in a co-primary manner, and inter-operator D2D communication is allocated over spectral resources contributed from both parties. In this paper, we consider a spectrum sharing scenario, where a number of OPs construct a spectrum pool dedicated to support inter-operator D2D communication. OPs negotiate in the form of a non-cooperative game about how much spectrum each OP contributes to the spectrum pool. OPs submit proposals to each other in parallel until a consensus is reached. When every OP has a concave utility function on the box-constrained region, we identify the conditions guaranteeing the existence of a unique equilibrium point. We show that the iterative algorithm based on the OP’s best response might not converge to the equilibrium point due to myopically overreacting to the response of the other OPs, while the Jacobi-play strategy update algorithm can converge with an appropriate selection of update parameter. Using the Jacobi-play update algorithm, we illustrate that asymmetric OPs contribute an unequal amount of resources to the spectrum pool; however, all participating OPs may experience significant performance gains compared with the scheme without spectrum sharing.

Exploiting Regional Differences: A Spatially Adaptive Random Access

In this paper, we discuss the potential for improvement of the simple random access scheme by utilizing local information such as the received signal-to-interference-plus-noise-ratio (SINR). We propose a spatially adaptive random access (SARA) scheme in which the transmitters in the network utilize different transmit probabilities depending on the local situation. In our proposed scheme, the transmit probability is adaptively updated by the ratio of the received SINR and the target SINR. We investigate the performance of the SARA scheme. For comparison, we derive an optimal transmit probability of ALOHA scheme in which all transmitters use the same transmit probability. We illustrate the performance of the SARA scheme through simulations. We show that the performance of the proposed scheme surpasses that of the optimal ALOHA scheme and is comparable with the CSMA/CA scheme.

Impact of Node Speed on Energy-Constrained Opportunistic Internet-of-Things with Wireless Power Transfer

Wireless power transfer (WPT) is a promising technology to realize the vision of Internet-of-Things (IoT) by powering energy-hungry IoT nodes by electromagnetic waves, overcoming the difficulty in battery recharging for massive numbers of nodes. Specifically, wireless charging stations (WCS) are deployed to transfer energy wirelessly to IoT nodes in the charging coverage. However, the coverage is restricted due to the limited hardware capability and safety issue, making mobile nodes have different battery charging patterns depending on their moving speeds. For example, slow moving nodes outside the coverage resort to waiting for energy charging from WCSs for a long time while those inside the coverage consistently recharge their batteries. On the other hand, fast moving nodes are able to receive energy within a relatively short waiting time. This paper investigates the above impact of node speed on energy provision and the resultant throughput of energy-constrained opportunistic IoT networks when data exchange between nodes are constrained by their intermittent connections as well as the levels of remaining energy. To this end, we design a two-dimensional Markov chain of which the state dimensions represent remaining energy and distance to the nearest WCS normalized by node speed, respectively. Solving this enables providing the following three insights. First, faster node speed makes the inter-meeting time between a node and a WCS shorter, leading to more frequent energy supply and higher throughput. Second, the above effect of node speed becomes marginal as the battery capacity increases. Finally, as nodes are more densely deployed, the throughput becomes scaling with the density ratio between mobiles and WCSs but independent of node speed, meaning that the throughput improvement from node speed disappears in dense networks. The results provide useful guidelines for IoT network provisioning and planning to achieve the maximum throughput performance given mobile environments.

Energy efficient mobile computation offloading via online prefetching

Conventional mobile computation offloading relies on offline prefetching that fetches user-specific data to the cloud prior to computing. For computing depending on real-time inputs, the offline operation can result in fetching large volumes of redundant data over wireless channels and unnecessarily consumes mobile-transmission energy. To address this issue, we propose the novel technique of online prefetching for a large-scale program with numerous tasks, which seamlessly integrates task-level computation prediction and real-time prefetching within the program runtime. The technique not only reduces mobile-energy consumption by avoiding excessive fetching but also shortens the program runtime by parallel fetching and computing enabled by prediction. By modeling the sequential task transition in an offloaded program as a Markov chain, stochastic optimization is applied to design the online-fetching policies to minimize mobile-energy consumption for transmitting fetched data over fading channels under a deadline constraint. The optimal policies for slow and fast fading are shown to have a similar threshold-based structure that selects candidates for the next task by applying a threshold on their likelihoods and furthermore uses them controlling the corresponding sizes of prefetched data. In addition, computation prediction for online prefetching is shown theoretically to always achieve energy reduction.

Cooperative transmissions in ultra-dense networks under a bounded dual-slope path loss model

In an ultra-dense network (UDN) where there are more base stations (BSs) than active users, it is possible that many BSs are instantaneously left idle. Thus, how to utilize these dormant BSs by means of cooperative transmission is an interesting question. In this paper, we investigate the performance of a UDN with two types of cooperation schemes: non-coherent joint transmission (JT) without channel state information (CSI) and coherent JT with full CSI knowledge. We consider a bounded dual-slope path loss model to describe UDN environments where a user has several BSs in the near-field and the rest in the far-field. Numerical results show that non-coherent JT cannot improve the user spectral efficiency (SE) due to the simultaneous increment in signal and interference powers. For coherent JT, the achievable SE gain depends on the range of near-field, the relative densities of BSs and users, and the CSI accuracy. Finally, we assess the energy efficiency (EE) of cooperation in UDN. Despite costing extra energy consumption, cooperation can still improve EE under certain conditions.