5G wireless networks are expected to usher in massive Machine Type Communications (mMTC) pertaining to the Internet of Things (IoT). A large fraction of the devices participating in IoT are likely to be low-power devices that generate sporadic traffic. It is anticipated that autonomous grant-free communications would be needed to accommodate these devices and the traffic they generate. Preamble transmission is a key part of such grant-free communications, and system performance including the desired power savings for the devices depends critically on the preamble detection-false alarm characteristics. In this context, low-power devices in extended coverage scenarios present a stiff challenge to system designers. In this study, we show that with narrowband resource allocations, use of preamble acknowledgements and judiciously set power control targets one can achieve the desired performance even for low-power devices in challenging scenarios.

Throughput performance of WiFi networks, which employ the Carrier Sense Multiple Access (CSMA) technique, can be estimated fairly accurately using Bianchi's analytic solution provided all elements of the network are within the carrier sensing range of one another. However, this solution cannot be applied to networks that are spread over a wide area. A paper by Liew, et al proposed an interesting approximate solution for such networks. While this solution was shown to work well in a variety of conditions, it suffers from a limitation in that it requires all transmitter-receiver pairs to have independent and identically distributed (i.i.d.) transmission times. In this paper, we generalize some of the key results of Liew, et al by removing the restriction on transmission times, which leads to a solution technique that can be used to analyze CSMA networks where different transmitter-receiver pairs operate at different bit rates. We also provide a few examples to illustrate how well this technique works in different settings and compare it with solutions based on other methods.

In this paper, we present a practical method to construct dirty paper coding (DPC) schemes using sum codes. Unlike the commonly used approach to DPC where the coding scheme involves concatenation of a channel code and a quantization code, the proposed method embodies a unified approach that emulates the binning method used in the proof of the DPC result. Auxiliary bits are used to create the desired number of code vectors in each bin. Sum codes are obtained when information sequences augmented with auxiliary bits are encoded using linear block codes. Sum-code-based DPC schemes can be implemented using any linear block code, and entail a relatively small increase in decoder complexity when compared to standard communication schemes. They can also lead to significant reduction in transmit power in comparison to standard schemes.

Base station cooperation has been shown to significantly mitigate the interference perceived in cellular networks and improve the quality of user experience. On the uplink, joint processing (JP) across antennas within a cluster of base stations yields significant gain, but requires significant backhaul to transport complex I & Q signals. The Network Interference Cancellation Engine (NICE) can yield throughput gains similar to that of JP, but with one to two orders of magnitude less backhaul. While NICE demonstrates significant potential for cellular networks, its performance has been evaluated under somewhat idealistic conditions. For instance, full buffer traffic has generally been assumed, thereby leading to a fully loaded system with strong interference. Bursty traffic may result in a partially loaded system with less interference and impact the gains of interference-mitigating techniques such as NICE. In addition, an ideal backhaul with negligible delay has generally been assumed. Delays in information exchanges between base stations may decrease the efficacy of base station cooperation. In this paper, the performance of NICE is evaluated under non full buffer traffic and non-ideal backhaul.

In this paper, we present a practical Dirty Paper Coding (DPC) scheme using sum codes based on LDPC codes. While a typical sum-code-based DPC scheme uses a constrained decoder as part of the encoding operation, such an approach fails in the case of LDPC codes since the constrained decoder based on a standard LDPC decoder tends to get stuck at highly suboptimal points in typical scenarios. We get around this difficulty via a simple code construction method based on bit-mapping or permutation. Examples included in this paper show that compared to standard communication schemes the proposed DPC scheme yields substantial savings in terms of the transmit energy required to attain desired error performance.

While the information theoretic result commonly referred to as “dirty paper coding” [1] has been known for long, it has not led to practical schemes that can be implemented easily in real-life communication systems. In this paper, we present the concept of sum codes and show how they provide a convenient platform for dirty paper coding. Comb-combined sum codes, which provide a convenient method of sum-code construction, are particularly useful in this respect. One can build comb-combined sum codes based on any linear block code to achieve reduction in the transmit energy required to attain a desired performance. Using an example based on tail-biting convolutional codes, we show how practical dirty paper coding may be implemented using any convenient linear block code.

Although the information theoretic result referred to as “dirty paper coding” [1] has been known for quite a while, it has not led to schemes that look attractive enough for real-life communication systems. In a companion paper [2], we presented the concept of sum codes and showed how they provide a convenient platform for interference suppression via dirty paper coding. In this paper, we present a dirty paper coding scheme based on trellis-coded modulation, which could be looked upon as an alternative to the sum-codes-based approach. Since trellis-coded modulation is designed for multi-level signal constellations, it is expected to work well as a platform for the proposed dirty paper coding scheme in which multi-level signal constellations play a critical role.

It is widely believed that cooperation among base stations can be employed to enhance the interference mitigation capability of base station receivers in cellular networks. Among the base station cooperation schemes that have been proposed to address the uplink interference problem, two promising ones are 1) Joint Multi-Cell MMSE Processing also referred to as Network MIMO; and 2) Multi-Cell Successive Interference Cancellation (MC-SIC). While both of these methods can substantially improve the performance of cellular networks, they have complementary strengths and limitations when implemented in a practical setting. In this paper, we propose a hybrid scheme called Generalized Network Interference Cancellation Engine, which combines the strengths of these two approaches while working within the constraints imposed by practical implementations. This view is borne out by the performance results presented in this paper.

The demand for high-rate wireless services grows unabated as new mobile devices and data-hungry applications continue to emerge. However, despite many advanced physical and link layer techniques that are employed in today's cellular networks, a large number of mobile users, especially at the cell edges, receive inadequate data rates due to high interference and path loss. Several techniques that exploit inter-base station cooperation have been proposed to address the inter-cell interference problem. While the initial studies show promising gains in idealized environments, it is important to analyze these techniques in a more realistic setting. This study provides detailed analyses of the benefits provided by uplink base station cooperation with several practical constraints and issues that would be encountered in a realistic cellular network deployment. Our results indicate that the cooperative signal processing techniques are robust to channel estimation errors given the pilot structure available in contemporary wireless systems. Furthermore, uplink cooperation can substantially improve the interference management capability of the cellular network, providing significant rate improvement over current non-cooperative networks.

Heterogeneous networks comprising overlapping layers of macro cells and small cells are expected to be widely deployed to cope with the rapidly increasing demand for wireless bandwidth. While judicious resource sharing and interference management mechanisms allow these networks to provide adequate performance for static or pedestrian users, they often fail to meet the needs of highly mobile users. In this paper, we propose a cooperative data transmission scheme called "Seamless Macro-Cell-Anchored Radio Transmission" that enables even highly mobile users to experience performance levels similar to those enjoyed by static users. The performance improvements effected by this scheme occur mainly at low percentiles; in that sense it can be said to deliver sustained end-user experience even to highly mobile users. Further improvement in edge performance is possible with the use of rate thresholds in conjunction with the proposed scheme.

Recently, there has been considerable interest in the potential of inter-base station cooperation techniques to manage excessive out-of-cell interference in evolving cellular networks. It has been observed that on the uplink, significant improvements in interference rejection can be attained by exchanging complex-valued received signal samples across a cluster of cells and employing joint multi-antenna receiver processing. However, such processing incurs substantial increases in backhaul overhead, exceeding the actual information delivered by at least an order of magnitude. In this paper, we propose and describe a signal processing approach based on a novel Network Interference Cancellation Engine (NICE), which opportunistically cancels out-of-cell interference by exchanging decoded dominant interferer data among cooperating cells and reconstructing interfering signals. Simulation results with NICE processing in cellular networks show that substantial improvements (5-7 dB) in signal-to-interference-plus-noise ratio may be achieved over current non-cooperative multi-antenna receiver processing techniques while allowing backhaul overhead to be reduced by factors on the order of 40 to 50 relative to joint processing techniques employing the exchange of complex-valued received signal samples.

Single frequency networks (SFN) in combination with a multi-carrier transmission scheme such as OFDM are often proposed as a means to provide continuous coverage of broadcast applications over a large area. In this paper, we propose a distributed beam-forming algorithm that makes use of channel state information fed back by receivers to improve the performance of the weaker connections. The distributed nature of the proposed algorithm makes it easier to implement when compared to its centralized counterparts. Simulation studies show that the proposed algorithm results in a significant improvement in the performance of SFNs supporting broadcast or multicast applications.

Single frequency networks (SFN) in combination with a multi-carrier transmission scheme such as OFDM are often proposed as a means to provide continuous coverage of broadcast applications over a large area. While this combination does succeed in providing continuous coverage, it has certain limitations. Specifically, at points where signals from multiple base-stations are received, the overall signal-to-noise ratio can be poor because of relative phase differences. In this paper, we show how, through the use of orthogonal space-time codes, this limitation of SFNs can be overcome to improve their overall performance. This scheme could be viewed as an ldquoopen-looprdquo implementation of multi-cell cooperative transmission.

Streaming media over wireless networks typically rely on end-to-end feedback from client devices to help media servers adjust to changing channel conditions. In rapidly fluctuating channel conditions, the client device may not be able to effectively track changes and report them to the server. Furthermore, bandwidth constraints often limit the frequency of end-to-end feedback. In order to overcome these constraints, we propose Clearmedia, a signaling proxy-based architecture for streaming media services over wireless networks. This architecture enables media servers to receive frequent and reliable feedback on network conditions, which leads to enhanced service quality. Our performance studies show that the Clearmedia architecture achieves improvement in several key performance metrics that are representative of end-user perceived video quality.

Voice-over-IP (VoIP) services are emerging as a promising business opportunity for multiple system operators (MSOs). Signaling delay is one of the most important quality metrics for VoIP services. For VoIP services over networks with HFC-based access, the contention delay experienced by requests associated with signaling packets often dominates the overall signaling delay. In this paper, we present a simple analytical method to characterize this delay. The analytical method combines a closed queuing network model with a saturation model for contention delay characterization. The mean delays obtained using this method compare well with simulation results. The results also yield useful insights into the engineering of upstream channels in HFC-based access networks.

CDMA wireless systems are believed to require smaller fade margins (than TDMA or FDMA systems) because of their ability to get into what is known as soft handoff. A mobile in soft handoff maintains simultaneous radio links with multiple base-stations which enables it to make use of the best quality leg most of the time. We present an analysis of fade margins for systems allowing soft handoffs (e.g. CDMA) and those where only hard handoffs are possible (e.g. FDMA, TDMA). Our analysis is based on a model for hard handoffs with hysteresis and connection delay, and validates the claim that systems permitting soft handoff indeed require smaller fade margins.

Detailed simulation results are presented to illustrate the throughput performance of various congestion control schemes that have been considered when using link access protocol D as the level-2 protocol. Three classes of adaptive window schemes, all of which use implicit detection, are examined. In all of them, receiving a REJECT frame (which is sent by the far end when it receives an out-of-sequence frame) is interpreted as a sign of congestion, and the control action taken by the end-systems is in the form of reducing their layer-2 window. It is shown that these schemes perform fairly well over a wide range of network parameters and traffic patterns, with one in particular providing a very robust performance over the range. It involves reducing the window size to 1/2 upon receiving a REJECT frame.>

This paper describes a hybrid model, combining both analytical and simulation techniques, which was developed to study the performance of a netted computer based system. The computer based system that was modeled is the Facility Assignment and Control System (FACS). This system is presently being deployed within several Bell Operating Companies to inventory and assign central office and outside plant facilities. A key feature of the model is its ability to characterize the dynamic nature of FACS. An understanding of this dynamic nature is necessary in establishing important operational guidelines such as allowable CPU utilization, levels of multiprogramming and priority of transaction processing. In addition, the model allows the user to investigate the sensitivity of the system to a wide range of conditions. Typical study items could include the effect of various load scenarios, ability of the system to meet performance objectives, and different hardware configurations. As part of this paper, both the practical aspects of modeling a netted computer based system and the theoretical development of the hybrid model are considered.

A problem in band-limited signal estimation is presented. The signal is assumed to be a band-limited sequence subject to an energy constraint. The observed signal components are assumed to be corrupted by the components of a discrete-time stochastic noise process with zero-mean and known antocorrelations. The error metric is the energy in a fixed linear combination of the error components. Linear estimators are considered, and an explicit expression for the optimal (in a min-max sense) estimation scheme is derived. An interesting feature of the optimal estimation scheme derived in this correspondence is that it is identical to one based on stochastic models for both the signal and the noise.

The representation of discrete-time waveforms as finite-energy sequences is a useful mathematical abstraction. A special class of finite-energy sequences, of particular interest to communication theorists, is the class of band-limited sequences. A linear estimation of technique for these sequences is presented. The observations are assumed to be corrupted by the components of a finite-energy, band-limited noise sequence not necessarily band-limited to the same frequencies as the signal sequence. The error metric for the estimation errors is assumed to be the energy in a linear functional of the error components, and the error-criterion, by which the merit of an estimation scheme is judged, is the maximal error over a class of band-limited and energy-constrained signal and noise sequences. An interesting finding is that the min-max estimation schemes described here have a structure similar to that of the familiar minimum mean-square error (MMSE) schemes which are designed to minimize some average error.