With the increasing demand for advanced autonomous driving, the available communication resources may become constrained over different geographic areas. In addition, due to dynamic channel variations and imperfect cell deployments, guaranteeing the required communication resources for data hungry and delay-sensitive applications in autonomous vehicles (AVs), along their entire trips, becomes challenging. To address these issues, the paper investigates the feasibility of a hybrid system-optimum and user-equilibrium AV traffic framework subject to communication constraints, as well as its performance gain. Within such a framework, the paper introduces the problems of communication-constrained routing (CCR) and traffic control (CCTC) in the context of infrastructure-assisted autonomous driving and presents respective solutions. For CCR, an efficient two-layered routing scheme is proposed which can provide optimal trip duration. Simulation results show that the routing scheme achieves a good balance between longer duration of communication coverage and acceptable source-to-destination travel time. For CCTC, it is shown that there exists an optimal AV speed on each road segment, as well as an optimal inter-AV distance and an optimal number of AVs in each cell, to maximize the road-network AV throughput within a single cell. Moreover, spectrum allocation is used to achieve Pareto-optimal road-network throughput across cells, and a new key performance index (KPI) is defined to evaluate the traffic control capability of cellular systems. Simulation results validate the improvement of AV throughput via the proposed CCTC solution.

The fifth generation (5G) wireless standard will support several new use cases and 10 to 100 times the performance of fourth generation (4G) systems. Because of the diverse applications for 5G, flexible solutions which can address conflicting requirements will be needed. In this paper, we propose a solution which enables the use of discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-s-OFDM) and OFDM, which address different requirements, using a common low-complexity reference symbol (RS) design. In this solution, the DFT-s-OFDM symbol contains RSs in the frequency domain that may be shared by a subsequent OFDM symbol. The proposed scheme is generated by puncturing the output of a DFT-spread block and replacing the punctured samples with RSs in frequency. We prove that puncturing the interleaved samples at the output of the DFT-spread operation equivalently introduces a periodic interference to the data symbols at the input of the DFT-spread operation. We show that the interference due to the puncturing can be removed with a low-complexity receiver by exploiting the zeros inserted to certain locations before the DFT-spread block at the transmitter. Simulation results support that the proposed scheme removes the error floor caused by the puncturing and achieves lower peak-to- average-power ratio than OFDM.

In this paper, we introduce a windowing technique, which provides optimal time-frequency containment and maximal adjacent channel interference (ACI) rejection for orthogonal frequency-division multiplexing (OFDM)-based systems. Instead of using a single pulse shape function for all subcarriers, multiple functions are considered in order to maximize the time-frequency containment of the OFDM waveform. The main strategy is to concentrate the spectrum of windowing functions into a given bandwidth while achieving maximum suppression in the out-of-band region. This is achieved by employing prolate-based windowing functions which give optimal spectral concentration for time-limited pulse shapes. The windowing functions are designed per-subcarrier basis in order to exploit available concentration band for each subcarrier. In addition, the proposed concept is considered for the receive filtering in the presence of ACI. It is shown that the optimal spectral concentration property also maximizes ACI rejection for OFDM receivers.

Recent progress in establishing the capability of radios to operate in full duplex mode on a single channel has been attracting growing attention from many researchers. We extend this work by considering the application to small cells, in particular resource-managed cellular systems similar to the TDD variant of LTE. We derive conditions where full duplex operation provides improved throughput compared to half duplex for a single cell scenario. We present a hybrid scheduler that defaults to half duplex operation but can assign full duplex timeslots when it is advantageous to do so. We compare the performance of such a scheduler with a traditional half duplex scheduler in terms of throughput and energy efficiency. Our simulation results show that we achieve as much as 81% of the capacity doubling promised by full duplex, with limitations deriving from interference effects specific to full duplex operation.

In an uncoordinated network, the link-level performance of a wireless receiver might degrade significantly due to the interference from other transmitters that share the same spectrum. As a solution, in this study, the concept of partially overlapping tones (POT) is introduced. In POT, interference energy observed at a victim receiver is mitigated by partially overlapping the individual subcarriers via an intentional carrier frequency offset between the links. It is argued that the self-interference arising due to the use of POT can be more easily addressed than the dominant other-user interference, potentially yielding higher spectral efficiencies with POT. Using a spatial Poisson point process based framework, a tractable bit error rate analysis is provided to demonstrate potential benefits emerging from POT in system-level scenarios.

Many cellular user equipments (UEs) today are able to access both the unlicensed band (e.g., via WiFi) and the cellular licensed band. However, in most regions of the world, they are not allowed to access both bands simultaneously for data communications - users can only choose either WiFi or cellular. In order to allow UEs to enjoy both bands at the same time, in our earlier work a framework for femtocells to simultaneously access both licensed and unlicensed bands was proposed. In this paper, the framework is extended to include strategies for femtocells to balance their traffic in licensed and unlicensed bands. The goal is to maximize the sum utility (i.e., user satisfaction) of femto and WiFi users while keeping the femto-to-macro interference below predefined thresholds. The optimal femto traffic balancing scheme is obtained and implemented in a network simulator which considers the activities and interactions of macro, femto and WiFi networks. Simulation results demonstrate that the proposed scheme significantly increases sum utility of all macro, femto and WiFi users, compared with the current practices where users can choose only one band (licensed or unlicensed).

Cellular operators have been offloading data traffic from their licensed bands to unlicensed bands through a large number of WiFi hotspots over the past years. Although this approach improves the cellular network capacity to some extent, it falls short of getting significant throughput gains. In this paper, it is argued that femtocells, covering a short range, can be a perfect platform to jointly exploit the merits of both licensed and unlicensed frequency bands. In particular, a framework is proposed for a femtocell to simultaneously access both licensed and unlicensed bands. The performance of coexisting femtocell and WiFi networks operating over a fully-utilized unlicensed band are analytically modeled and are verified via simulations. Impact of femtocell channel access parameters on the performance of WiFi and cellular networks is also investigated, shedding light on how a femtocell can best adjust its channel access parameters to coexist with incumbent unlicensed spectrum users like WiFi networks.

A system with multiple transmitters (i.e. base stations) and multiple receivers (mobile nodes) is considered. The transmitter-receiver pairs are assumed to operate using the same resources without any coordination and hence the receivers unavoidably experience interference from undesired transmitters. A MIMO relaying scheme is proposed to manage the interference in the network by judiciously optimizing the relay precoding matrix and aligning the interference at each receiver simultaneously. It is shown that the proposed scheme provides a closed-form optimal precoding matrix. Moreover, the numerical results for various scenarios show that the scheme performs better than the considered baseline schemes for most of the channel conditions.

Zero-forcing (ZF) beamforming, an efficient technique for multiuser MIMO systems, requires perfect channel state information to be available at the base station. This is achieved by quantizing the channel and feeding back the information with a limited number of bits. A challenge of this method is the large downlink signaling overhead, which is due to the large size of the codebook that can be used at the base station for ZF beamforming. In this paper, we first analyze this problem and then present a technique designing codebooks with reduced size and minimal performance degradation. We also define the associated procedures required for the system implementation. Simulation results show that the size of the eNodeB codebook can be substantially reduced with only a small (5%) penalty in performance.

An affine invariant function for object recognition is constructed from wavelet coefficients of the object boundary. In previous works, undecimated dyadic wavelet transform was used to construct affine invariant functions. In this paper, an algorithm based on decimated wavelet transform is developed to compute an affine invariant function. As a result computational complexity is reduced without decreasing recognition performance. Experimental results are presented.

In this paper, an affine invariant function is presented for object recognition from wavelet coefficients of the object boundary. In previous works, undecimated wavelet transform was used for affine invariant functions. In this paper, an algorithm based on decimated wavelet transform is developed to compute the affine invariant function. As a result, computational complexity is significantly reduced without decreasing recognition performance. Experimental results are presented.

The developments in wavelet theory have given rise to the wavelet thresholding method, for extracting a signal from noisy data. Multiwavelets, wavelets with several scaling functions, have been introduced and they offer simultaneous orthogonality, symmetry and short support; which is not possible with ordinary wavelets, also called scalar wavelets. This property makes multiwavelets more suitable for various signal processing applications, especially compression and denoising. Like scalar wavelets, multiwavelets can be realized as filterbanks, however the filterbanks are now matrix-valued; requiring two or more input streams, which can be accomplished by prefiltering. Several thresholding methods to be used with different multiwavelets for image denoising are presented. The performances of multiwavelets are compared with those of scalar wavelets. Simulations reveal that multiwavelet based image denoising schemes outperform wavelet based methods both subjectively and objectively.