Integrated sensing and communication (ISAC) is being discussed in 5G Release 19 and will likely be a critical component of 6G. In this paper we study ISAC for automotive applications. Specifically, we focus on adding sensing capability to a vehicle modem. Such additional capability will increase the value proposition of adding higher bands connectivity to vehicles. We perform a comprehensive study of challenges needed to enable automotive grade sensing in a vehicle modem, and propose solutions to those challenges. We show how cyclic prefix-orthogonal frequency division multiplexing (CP-OFDM), which is used for communication, can be combined with novel receive processing to meet (and even exceed) the automotive sensing requirements. Furthermore, we propose a two-stage resource allocation scheme to minimize the overhead needed for sensing. This simplifies the tradeoff between communication and sensing. We also perform system level simulations to quantify the impact of sensing interference on cellular communication. Finally, we carry out measurements to identify antenna placement that can be used for both communications and sensing. Then, we prototype our proposals to demonstrate automotive level sensing using CP-OFDM.

Using commodity WiFi data for applications such as indoor localization, object identification and tracking and channel sounding has recently gained considerable attention. We study the problem of channel impulse response (CIR) estimation from commodity WiFi channel state information (CSI). The accuracy of a CIR estimation method in this setup is limited by both the available channel bandwidth as well as various CSI distortions induced by the underlying hardware. We propose a multi-band splicing method that increases channel bandwidth by combining CSI data across multiple frequency bands. In order to compensate for the CSI distortions, we develop a per-band processing algorithm that is able to estimate the distortion parameters and remove them to yield the “clean” CSI. This algorithm incorporates the atomic norm denoising sparse recovery method to exploit channel sparsity. Splicing clean CSI over M frequency bands, we use orthogonal matching pursuit (OMP) as an estimation method to recover the sparse CIR with high (M-fold) resolution. Unlike previous works in the literature, our method does not appeal to any limiting assumption on the CIR (other than the widely accepted sparsity assumption) or any ad hoc processing for distortion removal. We show, empirically, that the proposed method outperforms the state of the art in terms of localization accuracy.

Numerical evidence suggests that compressive sensing (CS) approaches for wideband massive MIMO channel estimation can achieve very good performance with limited training overhead by exploiting the sparsity of the physical channel. However, analytical characterization of the (minimum) training overhead requirements is still an open issue. By observing that the wideband massive MIMO channel can be represented by a vector that is not simply sparse but has well defined structural properties, referred to as hierarchical sparsity, we propose low complexity channel estimators for the uplink multiuser scenario that take this property into account. By employing the framework of the hierarchical restricted isometry property, rigorous performance guarantees for these algorithms are provided suggesting concrete design goals for the user pilot sequences. For a specific design, we analytically characterize the scaling of the required pilot overhead with increasing number of antennas and bandwidth, revealing that, as long as the number of antennas is sufficiently large, it is independent of the per user channel sparsity level as well as the number of active users. These analytical insights are verified by simulations demonstrating also the superiority of the proposed algorithm over conventional CS algorithms that ignore the hierarchical sparsity property.

Towards reducing the training signaling overhead in large scale and dense cloud radio access networks (CRAN), various approaches have been proposed based on the channel sparsification assumption, namely, only a small subset of the deployed remote radio heads (RRHs) are of significance to any user in the system. Motivated by the potential of compressive sensing (CS) techniques in this setting, this paper provides a rigorous description of the performance limits of many practical CS algorithms by considering the performance of the, so called, oracle estimator, which knows a priori which RRHs are of significance but not their corresponding channel values. By using tools from stochastic geometry, a closed form analytical expression of the oracle estimator performance is obtained, averaged over distribution of RRH positions and channel statistics. Apart from a bound on practical CS algorithms, the analysis provides important design insights, e.g., on how the training sequence length affects performance, and identifies the operational conditions where the channel sparsification assumption is valid. It is shown that the latter is true only in operational conditions with sufficiently large path loss exponents.

Advances in cellular networks such as device-to-device communications and full-duplex radios, as well as the inherent elimination of intra-cell interference achieved by network-controlled multiple access schemes, motivate the investigation of the cross-mode interference properties under a guard region corresponding to the Voronoi cell of an access point (AP). By modeling the positions of interfering APs and user equipments (UEs) as Poisson distributed, analytical expressions for the statistics of the cross-mode interference generated by either APs or UEs are obtained based on appropriately defined density functions. The considered system model and analysis are general enough to capture many operational scenarios of practical interest, including conventional downlink/uplink transmissions with nearest AP association, as well as direct communication between UEs that do not necessarily lie in the same cell. Analysis provides insights on the level of protection offered by a Voronoi guard region and its dependence on type of interference and receiver position. Numerical examples demonstrate the validity/accuracy of the analysis in obtaining the system coverage probability for operational scenarios of practical interest.

Current application of carrier aggregation (CA), a key enabling technology for wideband communications over fragmented spectrum, is limited to only a small number of component carriers (CCs). However, wireless broadband connectivity of future networks requires the exploitation of multiple, contiguous, and non-contiguous CCs (NC-CCs). By considering a large number of aggregated NC-CCs, the concept of massive non-contiguous CA (NC-CA) is realized, which offers the highest flexibility in spectrum aggregation. In order to fully exploit the system-level benefits of massive NC-CA, transceivers capable of efficiently accommodating parallel transmissions over all of the available NC-CCs are required. This is a challenging task in which current NC-CA transceiver architectures, including the straightforward parallel chains implementation, fail to accomplish, as they suffer from scalability and efficiency issues. Focusing on the digital baseband processing part of the transceiver, this paper proposes an efficient filter-bank transceiver architecture able to accommodate a large number of NC-CCs with a small complexity increase compared with the ideal case of the transceiver operating on a single CC with the same aggregate bandwidth. Specification of this new architecture is cast as a filter design problem with minimal assumptions on transmitted waveform format, channel statistics, and decoding scheme, allowing for universally applicable designs. Both heuristic and optimal design methodologies are provided, the latter obtained using the notion of capacity mean square error as an appropriate performance/design metric. The performance of the proposed architecture is evaluated analytically, and a case study where it is applied for OFDM transmissions is provided.

This paper considers the problem of analytically assessing the maximum achievable rates (capacity) of orthogonal frequency division multiplexing (OFDM) transmissions when the receiver, for complexity reasons, only accounts for the common phase error (CPE) effect due to phase noise impairments with inter-carrier interference (ICI) treated as noise. By recognizing that the functional form of the CPE with respect to the phase noise realization is actually a free design parameter, determination of the capacity is posed as a functional optimization problem with respect to the, so-called, CPE function. A simple lower bound of the capacity is obtained, revealing the performance degradation due to the unknown CPE at the receiver, as well as the suboptimal performance achieved in severe phase noise conditions by the conventional CPE function that is routinely employed in previous works. The existence of an optimal number of subcarriers that balances the effects of the (unknown) CPE and ICI is highlighted and critical system design/operation issues, such as selection of the CPE function and effect of unknown channel on the achievable rate, are discussed. The analysis in this paper can be employed for determining the suitability of OFDM in phase noise channels and provides a tractable utility function for resource allocation purposes.

Recent trends in wireless networking such as small cells and network function virtualization, strongly suggest that the future cellular network will consist of many sub-networks controlled by self-interest operators competing for a share of the revenues associated with the high demand for service. This paper attempts to analyze the future network performance under these new market conditions, taking into account not only engineering properties of the sub-networks, e.g., spectral efficiency, but economic properties as well, i.e., service pricing. Going beyond previous related works, large scale infrastructure deployments over wide geographical areas, targeting a large number of users, are explicitly considered. The focus of the analysis is on the effects of different deployment densities (in units of average number of small cells per unit area) among competing operators as well as random placement of small cells. A game-theoretic system analysis is employed with market equilibrium characterization obtained analytically for the practical cases of two competing operators with arbitrary network characteristics and multiple competing operators with similar network characteristics. Closed form expressions for user and operator utilities at equilibrium are provided, revealing, among others, that extreme infrastructure densification, even though desirable from a purely engineering perspective, may not lead to stable market conditions under the considered competition model.

Inter-band carrier aggregation (CA) is considered as the key enabling technology towards a wideband communication system that can exploit and aggregate non-contiguous spectrum from heterogeneous bands. However, the commonly suggested transceiver design using independent baseband (signal processing) modules for each band (component carrier) is not efficient and scalable. This paper addresses this challenge, by proposing a new filter-bank based transceiver design, able to achieve CA of two component carriers using a single baseband module. Appropriate information-theoretic performance metrics are employed in order to obtain universal designs that are independent of modulation format, channel statistics and decoding scheme. Various design methodologies are considered, whose performance is investigated numerically and analytically. It is demonstrated that there exist transceiver designs achieving two-component CA with small additional complexity compared to the conventional single component carrier transmission.

An important enabler towards the successful introduction of any new element/feature to the cellular network, such as the ability to allow for direct, device-to-device (D2D) communications, is the investigation and characterization of the operational conditions, e.g., density of users, where its deployment will enhance performance. This paper attempts to provide a mathematically rigorous characterization of the set (region) of operational conditions, for which overlay D2D communications enhance performance in terms of average user rate. Using tools from stochastic geometry, and for the practically interesting case of a heavy loaded network, the operational region is identified in closed form as a function of a variety of parameters reflecting a wide range of operational conditions. It is shown that, under the appropriate deployment scheme, D2D communications can be beneficial not only in the typically assumed regime of “proximal communications” but to a wide range of operational conditions that include D2D link distances comparable to the distance from the cellular access point(s) as well as significantly large user densities.

An important enabler towards the successful deployment of any new element/feature to the cellular network is the investigation and characterization of the operational conditions where its introduction will enhance performance. Although there has been significant research activity on the potential of device-to-device (D2D) communications, there are currently no clear indications of whether D2D communications are actually able to provide benefits for a wide range of operational conditions, thus justifying their introduction to the system. This paper attempts to fill this gap by taking a stochastic geometry approach on characterizing the set (region) of operational conditions for which D2D communications enhance performance in terms of average user rate. For the practically interesting case of a heavy-loaded network, the operational region is provided in closed form as a function of a variety of parameters such as maximum D2D link distances and user densities, reflecting a wide range of operational conditions (points). It is shown that, under the appropriate deployment scheme, D2D communications can indeed be beneficial not only for the usually considered regime of “proximal communications” but to a wide range of operational conditions that include D2D link distances comparable to the distance to the cellular access point and considerably large user densities.

This paper examines the efficiency of spatial and frequency dimensions in serving multiple users in the downlink of a small cell wireless network with randomly deployed access points. For this purpose, the stochastic geometry framework is incorporated, taking into account the user distribution within each cell and the effect of sharing the available system resources to multiple users. An analysis of performance in terms of signal-to-interference-ratio and achieved user rate is provided that holds under the class of non-cooperative multiple access schemes. In order to obtain concrete results, two simple instances of multiple access schemes are considered. It is shown that performance depends critically on both the availability of frequency and/or spatial dimensions as well as the way they are employed. In particular, increasing the number of available frequency dimensions alone is beneficial for users experiencing large interference, whereas increasing spatial dimensions without employing frequency dimensions degrades performance. However, best performance is achieved when both dimensions are combined in serving the users.

This paper examines the impact of system parameters such as access point density and bandwidth partitioning on the performance of randomly deployed, interference-limited, dense wireless networks. While much progress has been achieved in analyzing randomly deployed networks via tools from stochastic geometry, most existing works either assume a very large user density compared to that of access points, which does not hold in a dense network, and/or consider only the user signal-to-interference-ratio as the system figure of merit, which provides only partial insight on user rate as the effect of multiple access is ignored. In this paper, the user rate distribution is obtained analytically, taking into account the effects of multiple access as well as the SIR outage. It is shown that user rate outage probability is dependent on the number of bandwidth partitions (subchannels) and the way they are utilized by the multiple access scheme. The optimal number of partitions is lower bounded for the case of large access point density. In addition, an upper bound of the minimum access point density required to provide an asymptotically small rate outage probability is provided in closed form.

The problem of resource allocation (RA) in a downlink OFDMA system with minimum user rate requests is examined under the realistic scenario of partial (imperfect) channel state information (CSI) at the base station. The challenge in this setting is the non-zero probability of outage events which may lead to significant performance degradation if algorithms assuming perfect CSI are utilized. In this paper the statistical description of the partial CSI is incorporated for deriving an (optimal) RA algorithm as the solution of an appropriate constrained optimization problem. Simplifications of the algorithm are utilized for significant complexity reduction with the additional property of allowing the system to adapt on-the-fly to time-varying minimum user rate requests.

The problem of resource allocation (RA) in a downlink OFDMA system is examined under the realistic assumption of imperfect channel state information (CSI) at the base station. In this case, there is a nonzero outage probability that the assigned rate at a particular subcarrier/user pair will not be supported by the true channel realization, which may lead to a significant waste of the system's available resources. It is therefore necessary to obtain RA algorithms that take into account the effect of imperfect CSI. By exploiting the statistical description of the imperfect CSI, various algorithms are proposed that tradeoff complexity versus performance, aiming at maximizing the system's successfully transmitted rate.

A new, reduced complexity algorithm is proposed for compensating the Inter-Carrier Interference (ICI) caused by severe PHase Noise (PHN) and Residual Frequency Offset (RFO) in OFDM systems. The algorithm estimates and compensates the most significant terms of the frequency domain ICI process, which are optimally selected via a Minimum Mean Squared Error (MMSE) criterion. The algorithm requires minimal knowledge of the phase process statistics, the estimation of which is also considered. The scheme outperforms previously proposed compensation methods of similar complexity, when severe phase impairments are present.