Shenghui Song

Maximizing energy efficiency in wireless networks with a minimum average throughput requirement

Given the growing concern over energy consumption and associated global warming, green communication is becoming more and more important. Lots of efforts have been put into investigating energy efficiency based design in wireless systems. Unfortunately, the maximum energy efficiency of a point-to-point link is normally achieved when the transmit power approaches zero, which, however, is not desirable in practical systems due to the low achievable data rate. In this paper, we consider the energy efficiency optimization with a practical power consumption model, where, besides a maximum transmit power constraint, we set a rate constraint (r0) to guarantee an average throughput requirement (Rth). Due to the possible outage in transmission, r0 is in general different from Rth, and determining r0 for a given Rth is not trivial. We shall derive a closed-form solution for the optimal transmit power that maximizes energy efficiency. We will also demonstrate that a carefully selected rate constraint r0 can guarantee the required average throughput Rth and provide the freedom to achieve different tradeoffs between energy efficiency and average throughput.

Localized or Interleaved? A Tradeoff between Diversity and CFO Interference in Multipath Channels

Carrier frequency offset (CFO) damages the orthogonality between sub-carriers and thus causes multiuser interference in uplink OFDMA/SC-FDMA systems. For a given CFO, such multiuser interference is mainly dictated by channel (sub-carrier) allocation, which also specifies the diversity gain of one user over multi-path channels. In particular, the positions of one users sub-channels will determine its diversity gain, while the distances between sub-channels of the concerned user and those of others will govern the CFO interference. Two popular channel allocation methods are the localized and interleaved (distributed) schemes where the former has less CFO interference but the latter achieves more diversity gain. In this paper, we will consider the channel allocation scheme for uplink LTE systems by investigating the effects of channel allocation on both of the diversity gain and CFO interference. By combining these two effects, we will propose a semi-interleaved scheme, which achieves full diversity gain with minimum CFO interference.

Cooperative Cognitive Networks: Optimal, Distributed and Low-Complexity Algorithms

This paper considers the cooperation between a cognitive system and a primary system where multiple cognitive base stations (CBSs) relay the primary users (PU) signals in exchange for more opportunity to transmit their own signals. The CBSs use amplify-and-forward (AF) relaying and coordinated beamforming to relay the primary signals and transmit their own signals. The objective is to minimize the overall transmit power of the CBSs given the rate requirements of the PU and the cognitive users (CUs). We show that the relaying matrices have unity rank and perform two functions: Matched filter receive beamforming and transmit beamforming. We then develop two efficient algorithms to find the optimal solution. The first one has a linear convergence rate and is suitable for distributed implementation, while the second one enjoys superlinear convergence but requires centralized processing. Further, we derive the beamforming vectors for the linear conventional zero-forcing (CZF) and prior zero-forcing (PZF) schemes, which provide much simpler solutions. Simulation results demonstrate the improvement in terms of outage performance due to the cooperation between the primary and cognitive systems.

A Systematic Procedure for Accurately Approximating Lognormal-Sum Distributions

Lognormal approximation to a sum of lognormal variables has been widely adopted in wireless communications, and its justification is based on the intuition that after taking a logarithm, a lognormal sum can converge to a Gaussian variable. In this paper, we show how to fit a lognormal sum with the best candidate from a large family of distributions, including the lognormal, by resorting to a systematic procedure of model selection and parameter estimation. It is found that, over a general parameter setting, a much better approximation for the lognormal sums in the log scale is given by the Pearson type-IV distribution whose parameters can easily be determined through simple arithmetic operations. Numerical examples are presented for illustration.

Multi-Dimensional Detector for UWB Ranging Systems in Dense Multipath Environments

The use of ultra wideband (UWB) technology for high-resolution ranging is widely addressed in the literature, and most these studies assume the use of a correlation detector to determine the arrival time of the first path component. The correlation detector well performs in environments without signal distortion. However, dense multi-path propagation and frequency selective fading, as encountered in a typical UWB environment, force the received UWB signal to behave like a random waveform. Such a waveform is multi-dimensional in the sense that any single preset template can only capture partial signal energy for ranging. In coping with this situation, we show in this paper how to use multi-dimensional detectors for enhancing the ranging performance. The superiority of the new detectors to the conventional one is theoretically analyzed and confirmed through simulations based on real UWB data.

Parsimonious correlated nonstationary models for real baseband UWB data

Few ultrawide-band (UWB) models directly fit original baseband UWB data to simultaneously account for their correlation structure, non-Gaussianity, and nonstationarity. The difficulty arises from the fact that no relevant result is available, even in multivariate statistical analysis. It also arises from the attempt to pursue the details of the mechanism that is imagined to be responsible for the generation of UWB data. The consequence is the modeling complexity, which makes it difficult to handle the received signal correlation on the basis of a single realization. Accordingly, various partial characterization is used in the literature instead by virtue of second-order statistics (such as power delay profile), nonparametric characteristics (such as zero-crossing rate), or their combination. In this paper, we take a different philosophy, which believes that the information in the received UWB data itself, as long as fully exploited, plus some simple physical intuition should suffice for the model identification and its parameter estimation. A received UWB signal is decomposed into three factor processes and each is parsimoniously parameterized. The application of the new model to data regeneration and receiver design is illustrated by using the real UWB data acquired by Intel and the TimeDomain Corporation.

Power-Delay Tradeoff in Multi-User Mobile-Edge Computing Systems

Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we investigate the tradeoff between two critical but conflicting objectives in multi-user MEC systems, namely, the power consumption of mobile devices and the execution delay of computation tasks. A power consumption minimization problem with task buffer stability constraints is formulated to investigate the tradeoff, and an online algorithm that decides the local execution and computation offloading policy is developed based on Lyapunov optimization. Specifically, at each time slot, the optimal frequencies of the local CPUs are obtained in closed forms, while the optimal transmit power and bandwidth allocation for computation offloading are determined with the Gauss-Seidel method. Performance analysis is conducted for the proposed algorithm, which indicates that the power consumption and execution delay obeys an

Mutual Information of Multipath Channels with Imperfect Channel Information

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Prior Zero Forcing for Cognitive Relaying

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Prior Zero-Forcing for Relaying Primary Signals in Cognitive Network

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