The Experts below are selected from a list of 115935 Experts worldwide ranked by ideXlab platform

Vincent Harold Poor - One of the best experts on this subject based on the ideXlab platform.

  • heterogeneous statistical qos driven resource allocation over mmwave massive mimo based 5g mobile wireless networks in the non asymptotic Regime
    IEEE Journal on Selected Areas in Communications, 2019
    Co-Authors: Xi Zhang, Jingqing Wang, Vincent Harold Poor
    Abstract:

    The statistical delay-bounded quality-of-service (QoS) theory has been developed to efficiently support multimedia transmissions over 5G wireless networks. On the other hand, unlike in Shannon’s information-theoretic formalism requiring infinite blocklength, finite blocklength coding (FBC) has recently emerged for error Control in the non-asymptotic Regime, guaranteeing stringent statistical QoS requirements in terms of both latency and reliability for ultra-reliable low-latency communications (URLLC) in 5G services. Moreover, integrated with FBC, millimeter wave (mmWave) massive multi-input multi-output (m-MIMO) schemes have been designed to significantly improve the performance in guaranteeing delay/error-rate bounded QoS. However, due to the complexity of modeling and solving the optimization problems over mmWave m-MIMO fading channels in the non-asymptotic error-Control Regime, it is challenging to derive an optimal resource allocation policy for maximizing $\epsilon$ -effective capacity to guarantee statistical delay/error-rate bounded QoS. To overcome the above problems, in this paper we propose heterogeneous statistical-QoS driven resource allocation policies for mmWave m-MIMO based 5G wireless networks in both asymptotic and non-asymptotic Regimes. In particular, we develop an mmWave m-MIMO based 5G wireless networks model to optimize the effective capacity for our proposed schemes. Our simulations show that our proposed schemes outperform the existing schemes in guaranteeing heterogeneous statistical delay/error-rate bounded QoS.

  • heterogeneous statistical qos driven resource allocation over mmwave massive mimo based 5g mobile wireless networks in the non asymptotic Regime
    IEEE Journal on Selected Areas in Communications, 2019
    Co-Authors: Xi Zhang, Jingqing Wang, Vincent Harold Poor
    Abstract:

    The statistical delay-bounded quality-of-service (QoS) technique has been developed to efficiently support multimedia data transmissions over 5G mobile wireless networks. On the other hand, unlike in Shannon’s theorem requiring the infinite blocklength, the finite blocklength coding (FBC) has recently emerged as a viable and powerful error-Control technique in the non-asymptotic Regime to enable short-packet communications which can meet the stringent statistical QoS requirements in terms of both latency and reliability for the ultra-reliable and low latency communications (URLLC) in 5G multimedia services. Moreover, integrated with FBC, millimeter wave (mmWave) massive multi-input multi-output (m-MIMO) schemes have been designed to significantly improve the performances for real-time traffics in guaranteeing QoS requirements for both delay and error-rate bounds. However, due to the complexity of modeling and solving the effective-capacity maximization problems over mmWave m-MIMO wireless fading channels in the non-asymptotic error-Control Regime, it is challenging to derive the optimal resource allocation policy for maximizing the effective capacity while guaranteeing statistical delay/error-rate bounded QoS requirements. To overcome the above-mentioned problems, in this paper we propose heterogeneous QoS-driven resource allocation policies for mmWave m-MIMO based 5G mobile wireless networks in both asymptotic and non-asymptotic error-Control Regimes. In particular, we develop the mmWave m-MIMO based 5G mobile wireless system models, and formulate and solve the effective-capacity optimization problems for our proposed schemes. We also conduct a set of simulation experiments, showing that our proposed schemes outperform the other existing schemes in terms of heterogeneous statistical delay/error-rate bounded QoS provisioning.

Xi Zhang - One of the best experts on this subject based on the ideXlab platform.

  • heterogeneous statistical qos driven resource allocation over mmwave massive mimo based 5g mobile wireless networks in the non asymptotic Regime
    IEEE Journal on Selected Areas in Communications, 2019
    Co-Authors: Xi Zhang, Jingqing Wang, Vincent Harold Poor
    Abstract:

    The statistical delay-bounded quality-of-service (QoS) theory has been developed to efficiently support multimedia transmissions over 5G wireless networks. On the other hand, unlike in Shannon’s information-theoretic formalism requiring infinite blocklength, finite blocklength coding (FBC) has recently emerged for error Control in the non-asymptotic Regime, guaranteeing stringent statistical QoS requirements in terms of both latency and reliability for ultra-reliable low-latency communications (URLLC) in 5G services. Moreover, integrated with FBC, millimeter wave (mmWave) massive multi-input multi-output (m-MIMO) schemes have been designed to significantly improve the performance in guaranteeing delay/error-rate bounded QoS. However, due to the complexity of modeling and solving the optimization problems over mmWave m-MIMO fading channels in the non-asymptotic error-Control Regime, it is challenging to derive an optimal resource allocation policy for maximizing $\epsilon$ -effective capacity to guarantee statistical delay/error-rate bounded QoS. To overcome the above problems, in this paper we propose heterogeneous statistical-QoS driven resource allocation policies for mmWave m-MIMO based 5G wireless networks in both asymptotic and non-asymptotic Regimes. In particular, we develop an mmWave m-MIMO based 5G wireless networks model to optimize the effective capacity for our proposed schemes. Our simulations show that our proposed schemes outperform the existing schemes in guaranteeing heterogeneous statistical delay/error-rate bounded QoS.

  • heterogeneous statistical qos driven resource allocation over mmwave massive mimo based 5g mobile wireless networks in the non asymptotic Regime
    IEEE Journal on Selected Areas in Communications, 2019
    Co-Authors: Xi Zhang, Jingqing Wang, Vincent Harold Poor
    Abstract:

    The statistical delay-bounded quality-of-service (QoS) technique has been developed to efficiently support multimedia data transmissions over 5G mobile wireless networks. On the other hand, unlike in Shannon’s theorem requiring the infinite blocklength, the finite blocklength coding (FBC) has recently emerged as a viable and powerful error-Control technique in the non-asymptotic Regime to enable short-packet communications which can meet the stringent statistical QoS requirements in terms of both latency and reliability for the ultra-reliable and low latency communications (URLLC) in 5G multimedia services. Moreover, integrated with FBC, millimeter wave (mmWave) massive multi-input multi-output (m-MIMO) schemes have been designed to significantly improve the performances for real-time traffics in guaranteeing QoS requirements for both delay and error-rate bounds. However, due to the complexity of modeling and solving the effective-capacity maximization problems over mmWave m-MIMO wireless fading channels in the non-asymptotic error-Control Regime, it is challenging to derive the optimal resource allocation policy for maximizing the effective capacity while guaranteeing statistical delay/error-rate bounded QoS requirements. To overcome the above-mentioned problems, in this paper we propose heterogeneous QoS-driven resource allocation policies for mmWave m-MIMO based 5G mobile wireless networks in both asymptotic and non-asymptotic error-Control Regimes. In particular, we develop the mmWave m-MIMO based 5G mobile wireless system models, and formulate and solve the effective-capacity optimization problems for our proposed schemes. We also conduct a set of simulation experiments, showing that our proposed schemes outperform the other existing schemes in terms of heterogeneous statistical delay/error-rate bounded QoS provisioning.

Jingqing Wang - One of the best experts on this subject based on the ideXlab platform.

  • heterogeneous statistical qos driven resource allocation over mmwave massive mimo based 5g mobile wireless networks in the non asymptotic Regime
    IEEE Journal on Selected Areas in Communications, 2019
    Co-Authors: Xi Zhang, Jingqing Wang, Vincent Harold Poor
    Abstract:

    The statistical delay-bounded quality-of-service (QoS) theory has been developed to efficiently support multimedia transmissions over 5G wireless networks. On the other hand, unlike in Shannon’s information-theoretic formalism requiring infinite blocklength, finite blocklength coding (FBC) has recently emerged for error Control in the non-asymptotic Regime, guaranteeing stringent statistical QoS requirements in terms of both latency and reliability for ultra-reliable low-latency communications (URLLC) in 5G services. Moreover, integrated with FBC, millimeter wave (mmWave) massive multi-input multi-output (m-MIMO) schemes have been designed to significantly improve the performance in guaranteeing delay/error-rate bounded QoS. However, due to the complexity of modeling and solving the optimization problems over mmWave m-MIMO fading channels in the non-asymptotic error-Control Regime, it is challenging to derive an optimal resource allocation policy for maximizing $\epsilon$ -effective capacity to guarantee statistical delay/error-rate bounded QoS. To overcome the above problems, in this paper we propose heterogeneous statistical-QoS driven resource allocation policies for mmWave m-MIMO based 5G wireless networks in both asymptotic and non-asymptotic Regimes. In particular, we develop an mmWave m-MIMO based 5G wireless networks model to optimize the effective capacity for our proposed schemes. Our simulations show that our proposed schemes outperform the existing schemes in guaranteeing heterogeneous statistical delay/error-rate bounded QoS.

  • heterogeneous statistical qos driven resource allocation over mmwave massive mimo based 5g mobile wireless networks in the non asymptotic Regime
    IEEE Journal on Selected Areas in Communications, 2019
    Co-Authors: Xi Zhang, Jingqing Wang, Vincent Harold Poor
    Abstract:

    The statistical delay-bounded quality-of-service (QoS) technique has been developed to efficiently support multimedia data transmissions over 5G mobile wireless networks. On the other hand, unlike in Shannon’s theorem requiring the infinite blocklength, the finite blocklength coding (FBC) has recently emerged as a viable and powerful error-Control technique in the non-asymptotic Regime to enable short-packet communications which can meet the stringent statistical QoS requirements in terms of both latency and reliability for the ultra-reliable and low latency communications (URLLC) in 5G multimedia services. Moreover, integrated with FBC, millimeter wave (mmWave) massive multi-input multi-output (m-MIMO) schemes have been designed to significantly improve the performances for real-time traffics in guaranteeing QoS requirements for both delay and error-rate bounds. However, due to the complexity of modeling and solving the effective-capacity maximization problems over mmWave m-MIMO wireless fading channels in the non-asymptotic error-Control Regime, it is challenging to derive the optimal resource allocation policy for maximizing the effective capacity while guaranteeing statistical delay/error-rate bounded QoS requirements. To overcome the above-mentioned problems, in this paper we propose heterogeneous QoS-driven resource allocation policies for mmWave m-MIMO based 5G mobile wireless networks in both asymptotic and non-asymptotic error-Control Regimes. In particular, we develop the mmWave m-MIMO based 5G mobile wireless system models, and formulate and solve the effective-capacity optimization problems for our proposed schemes. We also conduct a set of simulation experiments, showing that our proposed schemes outperform the other existing schemes in terms of heterogeneous statistical delay/error-rate bounded QoS provisioning.

Letizia Paoli - One of the best experts on this subject based on the ideXlab platform.

  • change is possible the history of the international drug Control Regime and implications for future policymaking
    Substance Use & Misuse, 2012
    Co-Authors: Letizia Paoli, Victoria A Greenfield, Peter Reuter
    Abstract:

    The article, based upon an extensive literature review, reconstructs and analyzes the parallel evolution of the international drug Control Regime and the world opiate market, assessing the impact of the former on the latter until the rise of present-day mass markets. It shows that, since its inception, the Regime has focused almost entirely on matters of supply. However, that focus has not always meant “prohibition”; until 1961, the key principle of the Regime was “regulation.” Given the different forms drug Control policy has taken in the past, the authors conclude it may be amenable to new forms in the future.

  • if supply oriented drug policy is broken can harm reduction help fix it melding disciplines and methods to advance international drug Control policy
    International Journal of Drug Policy, 2012
    Co-Authors: Victoria A Greenfield, Letizia Paoli
    Abstract:

    Critics of the international drug Control Regime contend that supply-oriented policy interventions are not just ineffective, but they also produce unintended adverse consequences. Research suggests their claims have merit. Lasting local reductions in opium production are possible, albeit rare; but, unless global demand shrinks, production will shift elsewhere, with little or no effect on the aggregate supply of heroin and, potentially, at some expense to exiting and newly emerging suppliers. The net consequences of the international drug Control Regime and related national policies are as yet unknown. In this paper, we consider whether “harm reduction,” a subject of intense debate in the demand-oriented drug policy community, can provide a unifying foundation for supply-oriented drug policy, one capable of speaking more directly to policy goals. Despite substantial conceptual and technical challenges, we find that harm reduction can provide a basis for assessing the net consequences of supply-oriented drug policy, choosing more rigorously among policy options, and identifying new policy options. In addition, we outline a practical path forward for assessing harms and policy options.

  • if supply oriented drug policy is broken can harm reduction help fix it melding disciplines and methods to advance international drug Control policy
    International Journal of Drug Policy, 2012
    Co-Authors: Victoria A Greenfield, Letizia Paoli
    Abstract:

    Critics of the international drug-Control Regime contend that supply-oriented policy interventions are not just ineffective, but, in focusing almost exclusively on supply reduction, they also produce unintended adverse consequences. Evidence from the world heroin market supports their claims. The balance of the effects of policy is yet unknown, but the prospect of adverse consequences underlies a central paradox of contemporary supply-oriented policy. In this paper, we evaluate whether harm reduction, a subject of intense debate in the demand-oriented drug-policy community, can provide a unifying foundation for supply-oriented drug policy and speak more directly to policy goals. Our analysis rests on an extensive review of the literature on harm reduction and draws insight from other policy communities' disciplines and methods. First, we explore the paradoxes of supply-oriented policy that initially motivated our interest in harm reduction; second, we consider the conceptual and technical challenges that have contributed to the debate on harm reduction and assess their relevance to a supply-oriented application; third, we examine responses to those challenges, i.e., various tools (taxonomies, models, and measurement strategies), that can be used to identify, categorize, and assess harms. Despite substantial conceptual and technical challenges, we find that harm reduction can provide a basis for assessing the net consequences of supply-oriented drug policy, choosing more rigorously amongst policy options, and identifying new options. In addition, we outline a practical path forward for assessing harms and policy options. On the basis of our analysis, we suggest pursuing a harm-based approach and making a clearer distinction between supply-oriented and supply-reduction policy.

Victoria A Greenfield - One of the best experts on this subject based on the ideXlab platform.

  • change is possible the history of the international drug Control Regime and implications for future policymaking
    Substance Use & Misuse, 2012
    Co-Authors: Letizia Paoli, Victoria A Greenfield, Peter Reuter
    Abstract:

    The article, based upon an extensive literature review, reconstructs and analyzes the parallel evolution of the international drug Control Regime and the world opiate market, assessing the impact of the former on the latter until the rise of present-day mass markets. It shows that, since its inception, the Regime has focused almost entirely on matters of supply. However, that focus has not always meant “prohibition”; until 1961, the key principle of the Regime was “regulation.” Given the different forms drug Control policy has taken in the past, the authors conclude it may be amenable to new forms in the future.

  • if supply oriented drug policy is broken can harm reduction help fix it melding disciplines and methods to advance international drug Control policy
    International Journal of Drug Policy, 2012
    Co-Authors: Victoria A Greenfield, Letizia Paoli
    Abstract:

    Critics of the international drug Control Regime contend that supply-oriented policy interventions are not just ineffective, but they also produce unintended adverse consequences. Research suggests their claims have merit. Lasting local reductions in opium production are possible, albeit rare; but, unless global demand shrinks, production will shift elsewhere, with little or no effect on the aggregate supply of heroin and, potentially, at some expense to exiting and newly emerging suppliers. The net consequences of the international drug Control Regime and related national policies are as yet unknown. In this paper, we consider whether “harm reduction,” a subject of intense debate in the demand-oriented drug policy community, can provide a unifying foundation for supply-oriented drug policy, one capable of speaking more directly to policy goals. Despite substantial conceptual and technical challenges, we find that harm reduction can provide a basis for assessing the net consequences of supply-oriented drug policy, choosing more rigorously among policy options, and identifying new policy options. In addition, we outline a practical path forward for assessing harms and policy options.

  • if supply oriented drug policy is broken can harm reduction help fix it melding disciplines and methods to advance international drug Control policy
    International Journal of Drug Policy, 2012
    Co-Authors: Victoria A Greenfield, Letizia Paoli
    Abstract:

    Critics of the international drug-Control Regime contend that supply-oriented policy interventions are not just ineffective, but, in focusing almost exclusively on supply reduction, they also produce unintended adverse consequences. Evidence from the world heroin market supports their claims. The balance of the effects of policy is yet unknown, but the prospect of adverse consequences underlies a central paradox of contemporary supply-oriented policy. In this paper, we evaluate whether harm reduction, a subject of intense debate in the demand-oriented drug-policy community, can provide a unifying foundation for supply-oriented drug policy and speak more directly to policy goals. Our analysis rests on an extensive review of the literature on harm reduction and draws insight from other policy communities' disciplines and methods. First, we explore the paradoxes of supply-oriented policy that initially motivated our interest in harm reduction; second, we consider the conceptual and technical challenges that have contributed to the debate on harm reduction and assess their relevance to a supply-oriented application; third, we examine responses to those challenges, i.e., various tools (taxonomies, models, and measurement strategies), that can be used to identify, categorize, and assess harms. Despite substantial conceptual and technical challenges, we find that harm reduction can provide a basis for assessing the net consequences of supply-oriented drug policy, choosing more rigorously amongst policy options, and identifying new options. In addition, we outline a practical path forward for assessing harms and policy options. On the basis of our analysis, we suggest pursuing a harm-based approach and making a clearer distinction between supply-oriented and supply-reduction policy.