We present two modulation and detection techniques that are designed to allow for efficient equalization for channels that exhibit an arbitrary Doppler spread but no delay spread. These techniques are based on principles similar to techniques designed for time-invariant delay spread channels (e.g., Orthogonal Frequency Division Multiplexing or OFDM) and have the same computational complexity. Through numerical simulations, we show that effective equalization is possible for channels that exhibit a high Doppler spread and even a modest delay spread, whereas equalized OFDM exhibits a strictly worse performance in these environments. Our results indicate that, in rapidly time-varying channels, such as those found in high-mobility or mmWave deployments, new modulation coupled with appropriate channel estimation and equalization techniques may significantly outperform modulation and detection schemes that are designed for static or slowly time varying multipath channels.

The scaling of coherent and non-coherent channel capacity is studied in a single-input multiple-output (SIMO) block Rayleigh fading channel as both the bandwidth and the number of receiver antennas go to infinity jointly with the transmit power fixed. The transmitter has no channel state information (CSI), while the receiver may have genie-provided CSI (coherent receiver), or the channel statistics only (non-coherent receiver). Our results show that if the available bandwidth is smaller than a threshold bandwidth which is proportional (up to leading order terms) to the square root of the number of antennas, there is no gap between the coherent capacity and the non-coherent capacity in terms of capacity scaling behavior. On the other hand, when the bandwidth is larger than this threshold, there is a capacity scaling gap. Since achievable rates using pilot symbols for channel estimation are subject to the non-coherent capacity bound, this work reveals that pilot-assisted coherent receivers in systems with a large number of receive antennas are unable to exploit excess spectrum above a given threshold for capacity gain.

The next generation of cellular networks are expected to support multiple user-oriented services that have various quality of service (QoS) requirements, yet must be serviced by a single infrastructure. To achieve this, network virtualization can play an important role by partitioning/slicing a single physical network resource into multiple virtual networks such that each of the slices can support various services independently. The main contribution of this work is an implementation of static and dynamic resource allocation schemes for different slices supporting different services. We use this implementation to study the effects of increasing the number of network slices on the number of optimization trigger events. Moreover, we propose a non-uniform resource sharing agreement (policy) between the participating network slices and investigate how these sharing agreements affect the frequency of optimization trigger events.

In this demo paper we present a dynamic spectrum-level slicing (DSLS) implementation for heterogeneous networks based on an open source software/hardware platform known as OpenAirInterface. Assuming the network traffic load changes every time interval, we mathematically formulate the DSLS as an optimization problem with the corresponding sets of constraints.

The performance gains from dynamic allocation of radio resources across multiple heterogeneous networks is studied. Through virtualization, the physical radio resources of the heterogeneous networks are first abstracted into a centralized pool of virtual radio resources. A dynamic spectrum-level slicing algorithm to share these radio resources across the different networks is then presented. This algorithm is responsive to changing user load and channel conditions. Simulation results show that for representative user arrival statistics, dynamic allocation of radio resources significantly lowers the percentage of dropped packets. In addition, they reveal that the triggers for dynamic allocation of resources across coexisting virtual networks occur every other time interval under the worst case traffic variation in the system (i.e., traffic varies every time interval). Our results suggest that performance benefits can be had even if dynamic spectrum-level slicing does not happen on time scales similar to that of the local resource schedulers residing in each virtual network.

We study diversity in one-shot communication over molecular timing channels. In the considered channel model the transmitter simultaneously releases a large number of information particles, where the information is encoded in the time of release. The receiver decodes the information based on the random time of arrival of the information particles. We characterize the asymptotic exponential decrease rate of the probability of error as a function of the number of released particles. We denote this quantity as the system diversity gain, as it depends both on the number of particles transmitted as well as the receiver detection method. Three types of detectors are considered: the maximum-likelihood (ML) detector, a linear detector, and a detector that is based on the first arrival (FA) among all the transmitted particles. We show that for random propagation characterized by right-sided unimodal densities with zero mode, the FA detector is equivalent to the ML detector, and significantly outperforms the linear detector. Moreover, even for densities with positive mode, the diversity gain achieved by the FA detector is very close to that achieved by the ML detector and much higher than the gain achieved by the linear detector.

A new modulation technique for the time-frequency dispersive channel is considered. The waveform construction, called Frequency-Domain Multiplexing with a Frequency-Domain Cyclic Prefix (FDM-FDCP) efficiently corrects for the Doppler spread introduced by the channel. The mathematical foundations behind this construction are described and efficient algorithms presented to modulate and demodulate information symbols. It is found that for channels with a high Doppler spread and a low delay spread, the construction can sustain good performance in terms of low SER and minimal overhead, whereas OFDM is strictly worse. This shows that, in rapidly time-varying time-frequency dispersive channels, general time-frequency signaling schemes (FDM-FDCP being an example) may outperform OFDM or other waveform constructions designed for multipath channels with low mobility.

In this work, energy coherence time, which is defined to be the coherence time of the channel quality information (CQI), is studied as a function of the number of antennas in a receiver with a large antenna array. It is found that, as a function of the number of receiver antennas, the energy coherence time can be much larger than the inverse of the Doppler frequency associated with the propagation environment. Numerical studies with representative values for cellular systems indicate that the net reduction in the frequency of adapting to changes in channel quality can be orders of magnitude higher with practical large antenna arrays.

We consider a noncoherent uplink and downlink with a large antenna array at the base station. The modulation used is ON-OFF keying, with symbol-by-symbol single-user detection. A ray tracing propagation model is assumed with knowledge at the base station and transmitters of only the ray arrival angles and amplitudes. We identify the sources of performance degradation, quantify notions of diversity gain (related to the detection error performance) and multiplexing gain (related to the number of users simultaneously supported), and present numerical results to demonstrate these gains. Our results indicate that in this noncoherent system, increasing the number of antenna elements can support multiple users, with a vanishing probability of detection error, as long as the number of users is below a certain threshold which increases with the number of antennas. This contrasts with the fact that in a rich scattering propagation environment, uncoded noncoherent systems performing symbol-by-symbol detection cannot support more than one user with a vanishing probability of error.

This work studies communication over diffusionbased molecular timing (DBMT) channels. The transmitter simultaneously releases multiple small information particles, where the information is encoded in the time of release. The receiver decodes the transmitted information based on the random time of arrival of the information particles, which is represented as an additive noise channel. For a DBMT channel, without flow, this noise follows the Levy distribution. Under this channel model, the maximum-likelihood (ML) detector is derived and shown to have high computational complexity. It is further shown that for any additive noise channel with -stable noise, α <; 1, such as the DBMT channel, a linear receiver is not able to take advantage of the release of multiple information particles. Thus, instead of the common low-complexity linear approach, a new detector, which is based on the first arrival (FA) among all the transmitted particles, is derived. Numerical simulations indicate that for a small to medium number of released particles, the performance of the FA detector is very close to the performance of the ML detector.

A system with a single antenna at the transmitter and receiver and no channel state information at either is considered. The channel experiences block Rayleigh fading with a coherence time of T0symbol times and the fading statistics are assumed to be known perfectly. The system operates with a finite average transmit power. It is shown that the capacity optimal input distribution in the T0-dimensional space is the product of the distribution of an isotropically-distributed unit vector and a distribution on the 2-norm in the T0-dimensional space which is discrete and has a finite number of points in the support. Numerical evaluations of this distribution and the associated capacity for a channel with fading and Gaussian noise for a coherence time T0= 2 are presented for representative SNRs.It is also shown numerically that an implicit channel estimation is done by the capacity-achieving scheme.

We consider a one-shot communication setting in which several single antenna transmitters communicate with a receiver with a large number of antennas, i.e., the receiver decodes transmitted information at the end of every symbol time. Motivated by the optimal noncoherent detector in a Rayleigh fading channel, we consider a noncoherent energy-based communication scheme that does not require any knowledge of instantaneous channel state information at either the transmitter or the receiver; it uses only the statistics of the channel and noise. We show that, for general channel fading statistics, the performance of the considered one-shot multiuser noncoherent scheme is the same, in a scaling law sense, as that of the optimal coherent scheme exploiting perfect channel knowledge and coding across time. Furthermore, we present a numerical evaluation of the performance of this scheme in representative fading and noise statistics.

An uplink system with a single antenna transmitter and a single receiver with a large number of antennas is considered. We propose a single-shot noncoherent scheme which does not use the instantaneous channel state information (CSI), but rather only the knowledge of the channel statistics, a transmitter that modulates information only in the amplitude of the symbols, and a receiver which measures only the average received energy across the antennas. This system model is motivated by the simplicity of the circuit design and the energy efficiency it entails for both the transmitter and the receiver. We propose constellation designs which are asymptotically optimal with respect to symbol error rate (SER) with an increasing number of antennas, for any finite signal-to-noise power ratio (SNR), under different assumptions on the availability of CSI statistics. We describe in detail the case when there is a bounded uncertainty on the moments of the fading distribution. We present the numerical results on the SER performance achieved by these designs and find that they outperform the existing amplitude-modulation-based noncoherent scheme of amplitude shift keying (ASK). They also achieve a smaller peak-to-average power ratio (PAPR) for scenarios with a low SNR or a large line-of-sight (LOS) component.

We consider one single-antenna transmitter communicating over a block-fading channel with a receiver that has a large number of antennas. We analyze coherent schemes with training overhead and noncoherent schemes with no training overhead. The latter systems only know the large scale fading statistics and the additive Gaussian noise power. In contrast to prior work on capacity characterizations of such systems, our approach is based on comparing error exponents with an increasing number of receive antennas. We provide an analytical lower bound on the error exponent for both coherent and noncoherent systems, and describe it explicitly for the case of a communication system with PSK constellations. Based on these analytic expressions, we show that noncoherent schemes can significantly outperform coherent schemes in channels with a strong line of sight component, low SNR or a short coherence time. We present numerical comparisons of our analytical BER performance bounds with Monte Carlo simulations for typical PSK constellations, system sizes and fading/noise statistics.

We consider one single antenna transmitter communicating with a receiver with a large number of antennas. Motivated by the optimal noncoherent detector in a Rayleigh fading channel, we propose a noncoherent energy-based communication scheme that does not require knowledge of instantaneous CSI (channel state information) at either the transmitter or the receiver; it uses only the statistics of the channel and noise. We explore the impact of coding to reduce the number of antennas needed for this system to achieve a given performance target. In particular, random coding error exponents for this system are used to determine tradeoff curves between the number of antennas and the blocklengths associated with a guaranteed performance target. However, since random codes have exponentially increasing decoding complexity with increasing blocklength, we also consider a simplified codebook design that has significantly lower encoding and decoding complexity. Simulations suggest that for small blocklengths, the performance of this simplified codebook is competitive with random coding constructions.

A single-input multiple-output (SIMO) multiple access channel with a large number of uncoded non-cooperating single antenna transmitters and joint processing at a finite precision multi-antenna receiver is considered. We fix the number of receiver antennas per transmitter and investigate the effects of receiver quantization on the recovery of the transmitted signals in the asymptotic limit of a large number of transmitters. Our results suggest that a very fine quantization resolution at the receiver antennas is not necessary; even a modest increase in the number of bits of quantization (with the number of transmitting users) is sufficient to guarantee asymptotic reliability.

This paper studies noncoherent wideband systems with a single antenna transmitter and a multiple antenna receiver with many elements, under signaling with peak-to-average power ratio constraints. The analysis considers the scaling behavior of capacity and achievable rates by letting both the number of antennas and the bandwidth go to infinity jointly. In contrast to prior work on wideband single input single output (SISO) channels without a-priori channel state information, it is shown that a sufficiently large number of receive antennas can make up for the vanishingly small SNR at each antenna. In particular, it is shown that when bandwidth grows sufficiently slowly with the number of antennas, the capacity scaling with an increasing number of receive antennas is the same as the optimal coherent capacity scaling. If the bandwidth grows faster than a certain threshold, however, the additional bandwidth does not help because a finite transmit power is spread over an excessively large bandwidth.

A single-input multiple-output multiple access channel, with a large number of uncoded noncooperating single-antenna transmitters and joint processing at a multiantenna receiver is considered. The minimum number of receiver antennas per transmitter that is needed for perfect recovery of the transmitted signals with overwhelming probability is investigated. It is shown that in the limit of a large number of transmitters, and in a rich scattering environment, the per-transmitter number of receiver antennas can be arbitrarily small, not only with the optimal maximum likelihood decoding rule, but also with much lower complexity decoders. Comparison with the ergodic capacity of the channel in the limit of a large number of transmitters suggests that uncoded transmissions achieve the Shannon-theoretic scaling behavior of the minimum per-transmitter number of receiver antennas. Thus, the diversity of a large system not only makes the performance metrics for some coded systems similar to that of uncoded systems, but also allows efficient decoders to realize close to the optimal performance of maximum likelihood decoding.

An uplink system with a single antenna transmitter and a single receiver with a large number of antennas is considered. For this system we propose an average energy-detection-based one-shot noncoherent communication scheme which does not use the instantaneous channel state information at either the transmitter or the receiver. We provide a constellation design that is asymptotically optimal in terms of achievable error exponent (in the number of receiver antennas) with an increasing constellation size. We also present numerical results on how this design performs in non-asymptotic regimes. Since the channel statistics may not be precisely known, we present a robust constellation design scheme which takes into account possible uncertainty in the large scale statistics and compare numerically its performance with the constellation design assuming perfect knowledge of channel and noise statistics. In terms of achievable symbol error rates, the robust constellation design is shown to perform almost as well as the scheme designed with perfectly known statistics despite mismatch in the channel statistics.

An uplink system with a fixed number of single antenna transmitters and a single receiver with a large number of antennas is considered. For this system we propose an energy-based noncoherent communication scheme that does not use instantaneous channel state information at either the transmitter or the receiver: only the channel and noise statistics are used.We show that, in terms of the scaling law of achievable symmetric rates for two users, our scheme's performance is no different from that achievable with perfect CSI (channel state information) at the transmitters and the receiver. We also provide a simple constellation design using the design criterion of minimum distance and present numerical results on how these designs perform in non-asymptotic regimes with typical channel and noise statistics.

We consider a multiple access channel with a large number of transmitters sending symbols from a constellation to the receiver of a multi-antenna base station. We investigate the joint decoding of the signals from all the users using a low complexity convex relaxation of the maximum likelihood decoder (constellation search). We show that, in a rich scattering environment, and in the asymptotic limit of a large number of transmitters, reliable communication is possible even without employing coding at the transmitters.

BACKGROUND: Next Generation Sequencing technologies have revolutionized many fields in biology by reducing the time and cost required for sequencing. As a result, large amounts of sequencing data are being generated. A typical sequencing data file may occupy tens or even hundreds of gigabytes of disk space, prohibitively large for many users. This data consists of both the nucleotide sequences and per-base quality scores that indicate the level of confidence in the readout of these sequences. Quality scores account for about half of the required disk space in the commonly used FASTQ format (before compression), and therefore the compression of the quality scores can significantly reduce storage requirements and speed up analysis and transmission of sequencing data. RESULTS: In this paper, we present a new scheme for the lossy compression of the quality scores, to address the problem of storage. Our framework allows the user to specify the rate (bits per quality score) prior to compression, independent of the data to be compressed. Our algorithm can work at any rate, unlike other lossy compression algorithms. We envisage our algorithm as being part of a more general compression scheme that works with the entire FASTQ file. Numerical experiments show that we can achieve a better mean squared error (MSE) for small rates (bits per quality score) than other lossy compression schemes. For the organism PhiX, whose assembled genome is known and assumed to be correct, we show that it is possible to achieve a significant reduction in size with little compromise in performance on downstream applications (e.g., alignment). CONCLUSIONS: QualComp is an open source software package, written in C and freely available for download at https://sourceforge.net/projects/qualcomp.

We propose a family of Secondary User (SU) power allocation schemes in spectrum sharing OFDM cognitive radio networks. The SU sum rates are maximized subject to a protection criterion for the Primary Users (PU) expressed through a utility function. We demonstrate that a specific choice of utility function leads to the maximization of weighted sum rate of all users, the weight being linked to a guarantee on the PU sum rate. Our formulation also allows trading off individual PU guarantees for higher SU sum rates, with a recently proposed scheme imposing individual PU Rate Loss guarantees being a limiting case.