Characterizing self-interference is essential to the design and evaluation of in-band full-duplex communication systems. Until now, little has been understood about this coupling in full-duplex systems operating at millimeter wave (mmWave) frequencies, and it has been shown that the highly-idealized models proposed for such do not align with practice. This work presents the first spatial and statistical model of mmWave self-interference backed by measurements, enabling engineers to draw realizations that exhibit the large-scale and small-scale spatial characteristics observed in our nearly 6.5 million measurements taken at 28 GHz. Core to our model is its use of system and model parameters having real-world meaning, which facilitates its extension to systems beyond our own phased array platform through proper parameterization. We demonstrate this by collecting nearly 13 million additional measurements to show that our model can generalize to two other system configurations. We assess our model by comparing it against actual measurements to confirm its ability to align spatially and in distribution with real-world self-interference. In addition, using both measurements and our model of self-interference, we evaluate an existing beamforming-based full-duplex mmWave solution to illustrate that our model can be reliably used to design new solutions and validate the performance improvements they may offer.

Communication in millimeter wave spectrum is an integral component to meet the ever increasing user throughput demand in fifth generation and beyond wireless cellular networks. Current millimeter wave basestation deployments typically use active phased array antennas which employ a codebook of predetermined directional beams to service cellular users. Highly directional beams are needed to overcome the high pathloss of the wireless medium in millimeter wave spectrum. However, drawbacks of such antenna systems include the signaling and measurement overhead required to select appropriate beams from the codebook for each user, as well as grouping users that can be covered by the same beam across the operating band of the array. Digital and hybrid beamforming systems are being actively researched to overcome these issues, however there is a scarcity of multi-antenna channel measurements in the millimeter wave spectrum needed to effectively optimize digital beamforming design parameters. In this paper, we present a novel fully digital 32 channel uniform planar array testbed, that is capable of performing wideband outdoor channel measurement in millimeter wave spectrum. Our testbed can also be calibrated to maintain precise phase and amplitude synchronization across all elements of the antenna array. Preliminary results from an outdoor channel sounding campaign show that digital beamforming receive algorithms provide significantly higher beamforming gain over traditional directional beamforming.

We present measurements of the 28 GHz self-interference channel for full-duplex sectorized multi-panel millimeter wave (mmWave) systems, such as integrated access and backhaul. We measure the isolation between the input of a transmitting phased array panel and the output of a co-located receiving phased array panel, each of which is electronically steered across a number of directions in azimuth and elevation. In total, nearly 6.5 million measurements were taken in an anechoic chamber to densely inspect the directional nature of the coupling between 256-element phased arrays. We observe that highly directional mmWave beams do not necessarily offer widespread high isolation between transmitting and receiving arrays. Rather, our measurements indicate that steering the transmitter or receiver away from the other tends to offer higher isolation but even slight steering changes can lead to drastic variations in isolation. These measurements can be useful references when developing mmWave full-duplex solutions and can motivate a variety of future topics including beam/user selection and beamforming codebook design.

Wireless communication in millimeter wave spectrum is poised to provide the latency and bandwidth needed for advanced use cases unfeasible at lower frequencies. Despite the market potential of vehicular communication networks, investigations into the millimeter wave vehicular channel are lacking. In this paper, we present a detailed overview of a novel 1 GHz wide, multi-antenna vehicle to vehicle directional channel sounding and measurement platform operating at 28 GHz. The channel sounder uses two 256-element phased arrays at the transmitter vehicle and four 64-element arrays at the receiver vehicle, with the receiver measuring 116 different directional beams in less than 1 millisecond. By measuring the full multi-beam channel impulse response at large bandwidths, our system provides unprecedented insight in instantaneous mobile vehicle to vehicle channels. The system also uses centimeter-level global position tracking and 360 degree video capture to provide additional contextual information for joint communication and sensing applications. An initial measurement campaign was conducted on highway and surface streets in Austin, Texas. We show example data that highlights the sensing capability of the system. Preliminary results from the measurement campaign show that bumper mounted mmWave arrays provide rich scattering in traffic as well a provide significant directional diversity aiding towards high reliability vehicular communication. Additionally, potential waveguide effects from high traffic in lanes can also extend the range of mmWave signals significantly.

Massive MIMO deployed with large channel bandwidths in mid-band spectrum is fundamental to high throughput and near ubiquitous coverage required by users in Fifth generation cellular networks. Network operators are also looking past existing monolithic radio access network architectures and looking towards functionally split architectures that allow for flexible, scalable, and cost-effective network deployments. Functional split of the baseband in massive MIMO deployments requires new and innovative approaches to distribute signal processing algorithms, and to optimize the information exchange across the fronthaul while maintaining acceptable levels of network performance. We consider a baseband split standardized by the Open RAN Foundation and investigate the issue of channel information being present at one side of the split, yet needed at the other side in order to perform uplink beamforming. We provide an analysis of air-interface performance degradation caused by the delay between determining beamforming weights from uplink sounding reference signals and applying these weights to the physical uplink shared channel. We also propose a novel beamforming weight design algorithm that can provide good tradeoff between air-interface performance and fronthaul throughput overhead. Our analysis and results are supported by both simulations and a massive MIMO prototyping testbed that emulates an outdoor environment with a high-speed user.

We provide a mutual information lower bound that can be used to analyze the effect of training in models with unknown parameters. For large-scale systems, we show that this bound can be calculated using the difference between two derivatives of a conditional entropy function. We provide a step-by-step process for computing the bound, and apply the steps to a quantized large-scale multiple-antenna wireless communication system with an unknown channel. Numerical results demonstrate the interplay between quantization and training.

Modern millimeter wave (mmWave) communication systems rely on beam alignment to deliver sufficient beamforming gain to close the link between devices. We present a novel beam selection methodology for multi-panel, full-duplex mmWave systems, which we call Steer, that delivers high beamforming gain while significantly reducing the full-duplex self-interference coupled between the transmit and receive beams. Steer does not necessitate changes to conventional beam alignment methodologies nor additional over-the-air feedback, making it compatible with existing cellular standards. Instead, Steer uses conventional beam alignment to identify the general directions beams should be steered, and then it makes use of a minimal number of self-interference measurements to jointly select transmit and receive beams that deliver high gain in these directions while coupling low self-interference. We implement Steer on an industry-grade 28 GHz phased array platform and use further simulation to show that full-duplex operation with beams selected by Steer can notably outperform both half-duplex and full-duplex operation with beams chosen via conventional beam selection. For instance, Steer can reliably reduce self-interference by more than 20 dB and improve SINR by more than 10 dB, compared to conventional beam selection. Our experimental results highlight that beam alignment can be used not only to deliver high beamforming gain in full-duplex mmWave systems but also to mitigate self-interference to levels near or below the noise floor, rendering additional self-interference cancellation unnecessary with Steer.

We present measurements and analysis of self-interference in multi-panel millimeter wave (mmWave) full-duplex communication systems at 28 GHz. In an anechoic chamber, we measure the self-interference power between the input of a transmitting phased array and the output of a colocated receiving phased array, each of which is electronically steered across a number of directions in azimuth and elevation. These self-interference power measurements shed light on the potential for a full-duplex communication system to successfully receive a desired signal while transmitting in-band. Our nearly 6.5 million measurements illustrate that more self-interference tends to be coupled when the transmitting and receiving phased arrays steer their beams toward one another but that slight shifts in steering direction (on the order of one degree) can lead to significant fluctuations in self-interference power. We analyze these measurements to characterize the spatial variability of self-interference to better quantify and statistically model this sensitivity. Our analyses and statistical results can be useful references when developing and evaluating mmWave full-duplex systems and motivate a variety of future topics including beam selection, beamforming codebook design, and self-interference channel modeling.

Millimeter wave wireless spectrum deployments will allow vehicular communications to share high data rate vehicular sensor data in real-time. The highly directional nature of wireless links in millimeter spectral bands will require continuous channel measurements to ensure the transmitter (TX) and receiver (RX) beams are aligned to provide the best channel. Using real-world vehicular mmWave measurement data at 28 GHz, we determine the optimal beam sweeping period, i.e. the frequency of the channel measurements, to align the RX beams to the best channel directions for maximizing the vehicle-to-infrastructure (V2I) throughput. We show that in a realistic vehicular traffic environment in Austin, TX, for a vehicle traveling at an average speed of 10.5 mph, a beam sweeping period of 300 ms in future V2I communication standards would maximize the V2I throughput, using a system of four RX phased arrays that scanned the channel 360 degrees in the azimuth and 30 degrees above and below the boresight. We also investigate the impact of the number of active RX chains controlling the steerable phased arrays on V2I throughput. Reducing the number of RX chains controlling the phased arrays helps reduce the cost of the vehicular mmWave hardware while multiple RX chains, although more expensive, provide more robustness to beam direction changes at the vehicle, allowing near maximum throughput over a wide range of beam sweep periods. We show that the overhead of utilizing one RX chain instead of four leads to a 10% drop in mean V2I throughput over six non-line-of-sight runs in real traffic conditions, with each run being 10 to 20 seconds long over a distance of 40 to 90 meters.

Characterization of the millimeter wave wireless channel is needed to facilitate fully connected vehicular communication in the future. To study the multipath-rich, rapidly varying nature of the vehicular propagation environment, fast millimeter wave channel sounders are required. We present a channel sounder design capable of covering 360 degrees in azimuth and 60 degrees in elevation with 200 individual beam directions in 6.25 ms by using four phased arrays simultaneously. The channel measurements are accompanied by high resolution positioning and video data, allowing channel sounding to be conducted while either the transmitter, or the receiver, or both are moving. Channel sounding campaigns were conducted at multiple urban locations with light traffic conditions in Austin, Texas. Preliminary results show that beam selection at the receiver can lower the effective pathloss exponent to 1.6 for line-of-sight and 2.25 for non line-of-sight.

We present FireSim, an open-source simulation platform that enables cycle-exact microarchitectural simulation of large scale-out clusters by combining FPGA-accelerated simulation of silicon-proven RTL designs with a scalable, distributed network simulation. Unlike prior FPGA-accelerated simulation tools, FireSim runs on Amazon EC2 F1, a public cloud FPGA platform, which greatly improves usability, provides elasticity, and lowers the cost of large-scale FPGA-based experiments. We describe the design and implementation of FireSim and show how it can provide sufficient performance to run modern applications at scale, to enable true hardware-software co-design. As an example, we demonstrate automatically generating and deploying a target cluster of 1,024 3.2 GHz quad-core server nodes, each with 16 GB of DRAM, interconnected by a 200 Gbit/s network with 2 microsecond latency, which simulates at a 3.4 MHz processor clock rate (less than 1,000x slowdown over real-time). In aggregate, this FireSim instantiation simulates 4,096 cores and 16 TB of memory, runs ~14 billion instructions per second, and harnesses 12.8 million dollars worth of FPGAs—at a total cost of only ~$100 per simulation hour to the user. We present several examples to show how FireSim can be used to explore various research directions in warehouse-scale machine design, including modeling networks with high-bandwidth and low-latency, integrating arbitrary RTL designs for a variety of commodity and specialized datacenter nodes, and modeling a variety of datacenter organizations, as well as reusing the scale-out FireSim infrastructure to enable fast, massively parallel cycle-exact single-node microarchitectural experimentation.

In this article, a novel method of performing subband analysis of digital signals is proposed. Conventional subband decomposition algorithms typically use a binary tree filterbank structure comprised of halfband filters. Due to design limitations of finite length filters, conventional decomposition algorithms typically suffer from interference due to aliasing. While longer halfband filters may reduce aliasing, such filters also increase latency and implementation complexity. Our proposed algorithm uses a novel structure of quadrature mirror filters to ensure aliasing is present outside of the spectral region of interest. Simulation results indicate that, compared to conventional algorithms, the proposed algorithm 1) reduces interference from aliasing by over 30dB, 2) reduces signal processing latency, and 3) reduces implementation complexity.

Many wireless data communication systems such as LTE, and Wi-Fi, are increasingly facing interference that is much stronger than thermal noise. Interference may arise due to dense spatial reuse of spectrum intended to increase user data rates, or from other devices emitting radiation in the same spectrum, or from electronic circuitry within the communication platform. For a multi-antenna receiver operating in an interference-limited channel, we evaluate four diversity combining algorithms in terms of outage probability in the low-outage regime. The contributions of this paper are (1) derivation of closed-form expressions for the output signal-to-interference ratio (SIR) statistics of fixed weight, maximal ratio, selection and post-detection combining; (2) comparison of the relative outage performance of these algorithms; and (3) proposed diversity combining algorithms to reduce outage probability. Our results can be applied in analyzing the outage performance and throughput capacity of both centralized and decentralized interference-limited wireless networks.

Channel shortening filters have been used in acoustics to reduce reverberation, in error control decoding to reduce complexity, and in communication systems to reduce inter-symbol interference. The cascade of a channel and a channel shortening filter would produce an overall impulse response that has more of the energy in the channel impulse response compacted into fewer adjacent samples. Once designed, channel shortening filters operate on a per-sample basis. In this paper, we evaluate sparse FIR filters, which use more design complexity and less per-sample processing complexity, for channel shortening. Our contributions include (1) proposing a new sparse FIR filter design method for channel shortening, and (2) evaluating design tradeoffs in energy compaction vs. implementation complexity for sparse and non-sparse FIR filters. Our simulation results for ADSL channels show that sparse designs could achieve the same energy compaction with half as many coefficients than non-sparse FIR filters for low filter orders.

With increasing spatial reuse of the radio spectrum, co-channel interference is becoming the dominant noise source and may severely degrade the communication performance of wireless transceivers. In this paper, we consider the problem of statistical-physical modeling of co-channel interference. Statistical modeling of interference is a useful tool to analyze the outage probabilities in wireless networks and to design interference-aware transceivers. Our contributions include (1) developing a unified framework to derive interference models for various wireless network environments, (2) demonstrating the applicability of the symmetric alpha stable and Middleton class A distributions in modeling co-channel interference in ad-hoc and cellular network environments, and (3) deriving analytical conditions on the system model parameters for which these distributions accurately model the statistical properties of the interference. Simulation results allow us to compare the key properties of empirical co-channel interference and their statistical models under different wireless network environments.

Multi-input multi-output (MIMO) receivers have generally been designed and their communication performance analyzed under the assumption of additive Gaussian noise. Wireless transceivers, however, may also be affected by radio frequency interference (RFI) that is well modeled using non-Gaussian impulsive statistics. In this paper, we derive bounds on the communication performance for a two transmit, two receive antenna MIMO system in the presence of RFI. Our contributions include derivation of (1) channel capacity in the presence of RFI, (2) probability of symbol error for uncoded transmissions, and (3) Chernoff bound on the pairwise error probability and cutoff rate as a measure of the throughput performance for coded transmissions. Comparison with the communication performance bounds for receivers designed assuming additive Gaussian noise demonstrates degradation in communication performance in the presence of RFI.

Multi-input multi-output (MIMO) receivers have been designed and their communication performance analyzed under the assumption of additive Gaussian noise. Wireless transceivers, however, may be affected by radio frequency interference (RFI) that is well modeled using non-Gaussian impulsive statistics. In this paper, we consider the problem of receiver design for a two transmit, two receive antenna MIMO system in the presence of RFI. First, we show that RFI is well modeled using a bivariate Middleton Class A model and validate the model with measured data. Using this RFI model, we demonstrate that conventional MIMO receivers experience significant degradation in communication performance. Then we derive the maximum likelihood (ML) receiver assuming bivariate Middleton Class A noise. Furthermore, we develop a parameter estimation method for this noise model and propose two sub-optimal ML receivers with reduced computational complexity. Simulations show significant improvement in symbol error rate performance of the proposed techniques over receivers designed assuming additive Gaussian noise.