A multimedia player that supports the DASH protocol has been developed for devices running either Android or Apple iOS. This media player is capable of supporting different profiles in the ISO Base Media File Format and MPEG-2 Transport Stream Media Segment Format. Our demonstration includes playback of live and VOD content, both of which are streamed from a web server located hundreds of miles away from the conference venue.

This paper explores the trade-offs of different levels of access control in a mixed femtocell-macrocell deployment with focus on reverse link (uplink) outage analysis. The aim is to identify and evaluate criteria that will help operators to assess the impact of allowing different degrees of access for macrocell users onto femtocells, and suggest some schemes that will be useful in this regard.

In this paper, we study the reverse link (RL) capacity of a co-channel macrocell-femtocell network, where the macrocell and femtocell networks share the same carrier. The analysis is done based on an outage probability criterion, and we use this analysis further to compare the capacities of different practical multi-carrier macrocell-femtocell deployment strategies.

Power control is a key air-interface management mechanism for any multiple-access CDMA-based wireless air-interface. Typically it has been used to ensure a target packet-error-rate (PER) for any user connection. In the presence of hybrid-ARQ (HARQ) on the reverse link (as in 3GPP2's EVDO-Rev A), there is additional flexibility that a power control implementation can utilize to ensure quality-of-service (QoS) for any connection. This paper discusses a general framework in which this can be done. It further provides an easily implement able algorithm within this framework, and substantiates its efficacy with simulations.

Uplink communication in a cellular radio network is considered where the base station in each cell employs linear or decision feedback multiuser receivers. We address the problem of minimizing the total of the user transmit powers over all linear or decision feedback multiuser receivers, such that all the users achieve their signal-to-interference ratio (SIR) targets. A distributed algorithm is obtained that is shown to converge, both in the deterministic and stochastic formulations, to the jointly optimal pair of power allocations and multiuser receivers.

A theory of noncoherent decision feedback multiuser detection for nonorthogonal binary modulation is developed that parallels that of coherent decision feedback multiuser detection for single-pulse modulation. In particular, an optimum noncoherent decision feedback detector is obtained that maximizes symmetric energy over a newly defined class of decision feedback detectors. Unlike the usual per-user performance metrics such as asymptotic efficiency or near-far resistance, the symmetric energy measure captures, with a single number, the asymptotic (high signal-to-noise ratio (SNR)) bit-error performance of all users at once. Several properties of the optimum decision feedback detector are established, one of which is that it outperforms the decision feedback generalized-likelihood ratio (GLR) detector in symmetric energy. It is also shown that, regardless of the order in which users are detected, the optimum noncoherent decision feedback detector outperforms its non-decision feedback counterpart in symmetric energy. Furthermore, two simple rules are obtained for determining the order in which users must be detected to guarantee that the optimum decision feedback detector outperforms its non-decision feedback counterpart (which in turn, is superior to the decorrelative GLR detector presented earlier) in terms of asymptotic effective energy for every user. In fact, one of the two (greedy) ordering rules also maximizes symmetric energy among all possible orderings. Such ordering rules are not available for the noncoherent decision feedback GLR detector in earlier work of the authors. Feasible sets of received energies are characterized in which it is possible, with power control, to achieve quality-of-service objectives for each user. None of the results in this paper make simplifying assumptions about the effects of error propagation. The term "noncoherent" in this work is used to denote that the receiver has no knowledge of the carrier phases and received signal energies of any of the users.

We consider blind adaptive multiuser detection in correlated waveform multiple-access-based cellular radio networks. A common stochastic approximation (SA)-based framework is proposed from which three blind adaptive algorithms for linear minimum mean squared error detection are obtained. Two of them coincide with previously proposed algorithms and the third is shown to be best suited for implementation at a base station. The work here also improves these SA-based adaptation algorithms in the context of cellular radio networks, in terms of the convergence properties by using the results on the SA technique with averaging. Convergence issues of the different adaptations are investigated and numerical examples are presented to demonstrate the performance improvement due to averaging.

Three noncoherent minimum mean-squared error (NMSE)-based multiuser receivers are proposed for multipulse modulation. These receivers have a common MMSE prefilter and are followed by one of three phase-independent decision rules. The simplest decision rule selects the maximum magnitude of the MMSE filter outputs, and the other two account for the second-order statistics of the residual multiple-access interference that remains after MMSE filtering. Blind adaptive algorithms are then proposed for the three noncoherent MMSE receivers. The common adaptive algorithm for the MMSE prefilter, which is based on the stochastic approximation method, is shown to converge in the mean-squared error sense to the nonblind NMSE prefilter. Our convergence analysis yields new insight into the tradeoff between the rate of convergence and the residual mean-squared error. The noncoherent blind receivers obtained here do not require the knowledge of the received signals of any of the interfering users, and are hence well-suited for distributed implementation in cellular wireless networks or in communication systems that must operate in noncooperative environments.

Uplink communication in a cellular radio network is considered where the base station in each cell employs linear or nonlinear (decision feedback) multiuser receivers. For any such receiver, the problem of interest is that of minimizing the total transmit power under the constraint that all the users of the network achieve their quality-of-service objective in terms of signal-to-interference ratio (SIR). When the solution is feasible for the desired SIR requirements, the optimum powers are computed with a distributed iterative power control strategy suitable for implementation at each base station. While the deterministic algorithm requires both in-cell and out-of-cell user information, the stochastic algorithm proposed in this paper can be implemented at the base stations in a truly distributed manner requiring knowledge of only in-cell parameters. Such an algorithm was proposed previously for the case where base stations use linear (single user) matched filter (MF) receivers. However, the feasibility region in terms of attainable SIRs for a well-designed multiuser receiver, particularly for a nonlinear receiver that employs decision feedback, is generally much larger than it is for the linear MF receiver. The stochastic power control algorithm in this paper, for linear or nonlinear multiuser receivers, converges in the mean-square sense to the minimal powers when the target SIRs are feasible. The second major focus of this paper is to improve the convergence properties of the conventional stochastic approximation based power control strategy by using the more recent results on averaging. Convergence issues of both the "nonaveraged" and "averaged" algorithms are investigated, and numerical examples are presented to demonstrate the performance improvement due to averaging.

Noncoherent multiuser detection for nonlinear modulation was previously studied and the idea of phase-independent noncoherent decorrelation was introduced and three post-decorrelative detectors were obtained and analyzed. However, their implementation requires the knowledge of the signature waveforms of all the users, which may be available only for centralized implementation. In this paper, we obtain a blind adaptive noncoherent decorrelative detector for nonlinear modulation that is suitable for distributed implementation with the knowledge of only the normalized signals of the desired user and the additive noise variance. This detector is based on the stochastic approximation method and does not require the overhead of any kind of "training." Two adaptive algorithms are developed, one guided by every signal in the desired user's signal set individually, and the other by the user's entire signal space. While this paper focuses on the particular problem of blind adaptive noncoherent decorrelative detection, it addresses a more general adaptation issue, namely, that of improving the convergence properties of an adaptive scheme by effectively using all the information that is known, and adapting only to the part of the desired solution that is truly unknown. Convergence is shown in the mean squared error sense for both the fixed step-size and time-varying step-size versions of the two algorithms.

The problem of noncoherent multiuser detection for multipulse modulation over the Gaussian multiuser channel is studied. It is assumed that neither the energies nor the carrier phases of the signals of any of the users are available at the receiver. Previously, a post-decorrelative generalized likelihood ratio test (GLRT) based detector was proposed as a solution to this problem. In this paper, we introduce the concept of noncoherent decision feedback (DF) that forms the basis for an improved solution to the same problem. The users are detected sequentially in some fixed order, and the decision for a particular user takes advantage of the reduction of uncertainty associated with the signal space resulting from decisions already made for previous users. In contrast to coherent DF, therefore, the feedforward and feedback transformations in the noncoherent case are themselves functions of the matched filter outputs. An efficient implementation of the noncoherent DF detector for M-ary modulation and /spl rho/-dimensional signal space requires O(M/sub /spl rho//) computational complexity per user. Upper and lower bounds on its symbol error probability are obtained. It is shown that significant improvements over the post-decorrelative GLRT-based detector are often possible. Sufficient conditions are obtained which guarantee, without ignoring error-propagation effects, that the high signal-to-noise performance of the DF strategy can be as good as its genie-aided version in which perfect past users' decisions are used.