We present a novel access protocol for crowd scenarios in massive multiple-input multiple-output (MIMO) systems. Crowd scenarios are characterized by a large number of users with intermittent access behavior, whereas orthogonal scheduling is infeasible. In such scenarios, random access is a natural choice. The proposed access protocol relies on two essential properties of a massive MIMO system, namely, asymptotic orthogonality between user channels and asymptotic invariance of channel powers. Signal processing techniques that take advantage of these properties allow us to view a set of contaminated pilot signals as a graph code on which iterative belief propagation can be performed. This makes it possible to decontaminate pilot signals and increase the throughput of the system. Numerical evaluations show that the proposed access protocol increases the throughput by 36%, when there are 400 antennas at the base station, compared to the conventional method of slotted Additive Links On-line Hawaii Area. With 1024 antennas, the throughput is increased by 85%.

The massive multiple-input multiple-output (MIMO) technology has great potential to manage the rapid growth of wireless data traffic. Massive MIMO achieves tremendous spectral efficiency by spatial multiplexing many tens of user equipments (UEs). These gains are only achieved in practice if many more UEs can connect efficiently to the network than today. As the number of UEs increases, while each UE intermittently accesses the network, the random access functionality becomes essential to share the limited number of pilots among the UEs. In this paper, we revisit the random access problem in the Massive MIMO context and develop a reengineered protocol, termedstrongest-user collision resolution(SUCRe). An accessing UE asks for a dedicated pilot by sending an uncoordinated random access pilot, with a risk that other UEs send the same pilot. The favorable propagation of massive MIMO channels is utilized to enable distributed collision detection at each UE, thereby determining the strength of the contenders’ signals and deciding to repeat the pilot if the UE judges that its signal at the receiver is the strongest. The SUCRe protocol resolves the vast majority of all pilot collisions in crowded urban scenarios and continues to admit UEs efficiently in overloaded networks.

A massive MIMO system, represented by a base station with hundreds of antennas, is capable of spatially multiplexing many devices and thus naturally suited to serve dense crowds of wireless devices in emerging applications, such as machine-type communications. Crowd scenarios pose new challenges in the pilot-based acquisition of channel state information and call for pilot access protocols that match the intermittent pattern of device activity. A joint pilot assignment and data transmission protocol based on random access is proposed in this paper for the uplink of a massive MIMO system. The protocol relies on the averaging across multiple transmission slots of the pilot collision events that result from the random access process. We derive new uplink sum rate expressions that take pilot collisions, intermittent device activity, and interference into account. Simplified bounds are obtained and used to optimize the device activation probability and pilot length. A performance analysis indicates how performance scales as a function of the number of antennas and the transmission slot duration.

This work concerns wireless cellular networks applying massive multiple-input multiple-output (MIMO) technology. In such a system, the base station in a given cell is equipped with a very large number (hundreds or even thousands) of antennas and serves multiple users. Estimation of the channel from the base station to each user is performed at the base station using an uplink pilot sequence. Such a channel estimation procedure suffers from pilot contamination. Orthogonal pilot sequences are used in a given cell but, due to the shortage of orthogonal sequences, the same pilot sequences must be reused in neighboring cells, causing pilot contamination. The solution presented in this paper suppresses pilot contamination, without the need for coordination among cells. Pilot sequence hopping is performed at each transmission slot, which provides a randomization of the pilot contamination. Using a modified Kaiman filter, it is shown that such randomized contamination can be significantly suppressed. Comparisons with conventional estimation methods show that the mean squared error can be lowered as much as an order of magnitude at low mobility.

This paper presents a novel framework, which enables a design of rateless codes for binary input additive white Gaussian noise (BIAWGN) channels, using the ripple-based approach known from the works for the binary erasure channel (BEC). We reveal that several aspects of the analytical results from the BEC also hold in BIAWGN channels. The presented framework is applied in a code design example, which shows promising results compared to existing work. In particular it shows a great robustness towards variations in the signal-to-noise power ratio (SNR), contrary to existing codes.

This paper presents a novel approach to multiple access control called coded splitting tree protocol. The approach builds on the known tree splitting protocols, code structure and successive interference cancellation (SIC). Several instances of the tree splitting protocol are initiated, each instance is terminated prematurely and subsequently iterated. The combined set of leaves from all the tree instances can then be viewed as a graph code, which is decodable using belief propagation. The main design problem is determining the order of splitting, which enables successful decoding as early as possible. Evaluations show that the proposed protocol provides considerable gains over the standard tree splitting protocol applying SIC. The improvement comes at the expense of an increased feedback and receiver complexity.

This paper proposes a concept called rateless feedback coding. We redesign the existing LT and Raptor codes, by introducing new degree distributions for the case when a few feedback opportunities are available. We show that incorporating feedback to LT codes can significantly decrease both the coding overhead and the encoding/decoding complexity. Moreover, we show that, at the price of a slight increase in the coding overhead, linear complexity is achieved with Raptor feedback coding.

In this paper, we present an analytical framework for designing LT codes in additive white Gaussian noise (AWGN) channels. We show that some of analytical results from binary erasure channels (BEC) also hold in AWGN channels with slight modifications. This enables us to apply a ripple-based design approach, which until now has only been used in the BEC. LT codes designed by this way show promising performance which is near the Shannon limit even with short codewords.

In this paper feedback in LT codes is investigated. The considered type of feedback is acknowledgments, where information on which symbols have been decoded is given to the transmitter. Our analysis reveals that acknowledgments has a very low potential in LT codes with standard degree distributions. Motivated by this, we analyze the impact of acknowledgments on multi-layer LT codes. In this case, feedback proves advantageous. By using only a single feedback message, it is possible to achieve a significant performance improvement compared to traditional LT codes.

In this paper we propose a new design of LT codes, which decreases the amount of necessary overhead in comparison to existing designs. The design focuses on a parameter of the LT decoding process called the ripple size. This parameter was also a key element in the design proposed in the original work by Luby. Specifically, Luby argued that an LT code should provide a constant ripple size during decoding. In this work we show that the ripple size should decrease during decoding, in order to reduce the necessary overhead. Initially we motivate this claim by analytical results related to the redundancy within an LT code. We then propose a new design procedure, which can provide any desired achievable decreasing ripple size. The new design procedure is evaluated and compared to the current state of the art through simulations. This reveals a significant increase in performance with respect to both average overhead and error probability at any fixed overhead.

This paper concerns multi path video streaming using adaptive multiple description coding. The adaptation leverages on the fact that multiple descriptions are correlated. Thus if an intermediate node gets feedback telling that another path is likely to deliver a description, this node can compress its description and forward it. Such a compression can also be done already at the source node; however, the feedback arrives more timely and reliably to intermediate nodes that are closer to the final receiver. In this paper we investigate the performance of such adaptation at the source node and an intermediate node, respectively. A trade-off exists between reducing the delay of the feedback by adapting in the vicinity of the receiver and increasing the gain from compression by adapting close to the source. The analysis shows that adaptation in the network provides a better trade-off than adaptation at the source. Schemes which provide simple solutions to adaptation both at the source and in the network are proposed, analyzed, simulated and compared to non-adaptive reference schemes in scenarios that involve last hop that is wireless. The results reveal that the proposed compression schemes offer significant benefits in streaming scenarios.

Media content distribution constitutes a growing share of the services on the Internet. Two distinct distribution approaches used today are layered coding (LC) and multiple description coding (MDC). Current wireless connection technologies, e.g. Wimax, have properties which make them unsuitable for media distribution using traditional approaches. In particular, the asymmetric relationship between the uplink and the downlink bandwidth makes the cooperative distribution difficult. A promising concept, termed MDC with Conditional Compression (MDC-CC), has been proposed [11], which essentially acts as an adaptive hybrid between LC and MDC. In order to facilitate the use of MDC-CC, a new overlay network approach is proposed, using tree of meshes. A control system for managing description distribution and compression in a small mesh is implemented in the discrete event simulator NS-2. The two traditional approaches, MDC and LC, are used as references for the performance evaluation of the proposed scheme. The system is simulated in a heterogeneous network environment, where packet errors are introduced. Moreover, a test is performed at different network loads. Performance gain is shown over both LC and MDC.