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Upcoming low-latency machine-to-machine (M2M) applications are currently attracting a significant amount of interest from the wireless networking research community. The design challenge with respect to such future applications is to allow wireless networks to operate extremely reliably at very short deadlines for rather small packets. To date, it is unclear how to design wireless networks efficiently for such novel requirements. One reason is that existing performance models for wireless networks often assume that the rate of the channel code is equal to the Shannon capacity. However, this model does not hold anymore when the packet size and thus blocklength of the channel code is small. Although it is known that finite blocklength has a major impact on the physical layer performance, we lack higher-layer performance models which account in particular for the queueing effects under the finite blocklength regime. A recently developed methodology provides probabilistic higher-layer delay bounds for fading channels when assuming transmission at the Shannon capacity limit. Based on this novel approach, we develop service process characterizations for fading channels with finite blocklength channel coding, leading to novel probabilistic delay bounds that can give a fundamental insight into the capabilities and limitations of wireless networks when facing low-latency M2M applications. In particular, we show that the Shannon capacity model significantly overestimates the delay performance for such applications, which would lead to insufficient resource allocations. Finally, based on our (validated) analytical model, we study various important parameter trade-offs highlighting the sensitivity of the delay distribution under the finite blocklength regime., Qc 20160323

Upcoming low-latency machine-to-machine (M2M) applications are currently attracting a significant amount of interest from the wireless networking research community. The design challenge with respect to such future applications is to allow wireless networks to operate extremely reliably at very short deadlines for rather small packets. To date, it is unclear how to design wireless networks efficiently for such novel requirements. One reason is that existing performance models for wireless networks often assume that the rate of the channel code is equal to the Shannon capacity. However, this model does not hold anymore when the packet size and thus blocklength of the channel code is small. Although it is known that finite blocklength has a major impact on the physical layer performance, we lack higher-layer performance models which account in particular for the queueing effects under the finite blocklength regime. A recently developed methodology provides probabilistic higher-layer delay bounds for fading channels when assuming transmission at the Shannon capacity limit. Based on this novel approach, we develop service process characterizations for fading channels with finite blocklength channel coding, leading to novel probabilistic delay bounds that can give a fundamental insight into the capabilities and limitations of wireless networks when facing low-latency M2M applications. In particular, we show that the Shannon capacity model significantly overestimates the delay performance for such applications, which would lead to insufficient resource allocations. Finally, based on our (validated) analytical model, we study various important parameter trade-offs highlighting the sensitivity of the delay distribution under the finite blocklength regime., Qc 20160323

Upcoming low-latency machine-to-machine (M2M) applications are currently attracting a significant amount of interest from the wireless networking research community. The design challenge with respect to such future applications is to allow wireless networks to operate extremely reliably at very short deadlines for rather small packets. To date, it is unclear how to design wireless networks efficiently for such novel requirements. One reason is that existing performance models for wireless networks often assume that the rate of the channel code is equal to the Shannon capacity. However, this model does not hold anymore when the packet size and thus blocklength of the channel code is small. Although it is known that finite blocklength has a major impact on the physical layer performance, we lack higher-layer performance models which account in particular for the queueing effects under the finite blocklength regime. A recently developed methodology provides probabilistic higher-layer delay bounds for fading channels when assuming transmission at the Shannon capacity limit. Based on this novel approach, we develop service process characterizations for fading channels with finite blocklength channel coding, leading to novel probabilistic delay bounds that can give a fundamental insight into the capabilities and limitations of wireless networks when facing low-latency M2M applications. In particular, we show that the Shannon capacity model significantly overestimates the delay performance for such applications, which would lead to insufficient resource allocations. Finally, based on our (validated) analytical model, we study various important parameter trade-offs highlighting the sensitivity of the delay distribution under the finite blocklength regime., Qc 20160323

Upcoming low-latency machine-to-machine (M2M) applications are currently attracting a significant amount of interest from the wireless networking research community. The design challenge with respect to such future applications is to allow wireless networks to operate extremely reliably at very short deadlines for rather small packets. To date, it is unclear how to design wireless networks efficiently for such novel requirements. One reason is that existing performance models for wireless networks often assume that the rate of the channel code is equal to the Shannon capacity. However, this model does not hold anymore when the packet size and thus blocklength of the channel code is small. Although it is known that finite blocklength has a major impact on the physical layer performance, we lack higher-layer performance models which account in particular for the queueing effects under the finite blocklength regime. A recently developed methodology provides probabilistic higher-layer delay bounds for fading channels when assuming transmission at the Shannon capacity limit. Based on this novel approach, we develop service process characterizations for fading channels with finite blocklength channel coding, leading to novel probabilistic delay bounds that can give a fundamental insight into the capabilities and limitations of wireless networks when facing low-latency M2M applications. In particular, we show that the Shannon capacity model significantly overestimates the delay performance for such applications, which would lead to insufficient resource allocations. Finally, based on our (validated) analytical model, we study various important parameter trade-offs highlighting the sensitivity of the delay distribution under the finite blocklength regime., Qc 20160323

Upcoming low-latency machine-to-machine (M2M) applications are currently attracting a significant amount of interest from the wireless networking research community. The design challenge with respect to such future applications is to allow wireless networks to operate extremely reliably at very short deadlines for rather small packets. To date, it is unclear how to design wireless networks efficiently for such novel requirements. One reason is that existing performance models for wireless networks often assume that the rate of the channel code is equal to the Shannon capacity. However, this model does not hold anymore when the packet size and thus blocklength of the channel code is small. Although it is known that finite blocklength has a major impact on the physical layer performance, we lack higher-layer performance models which account in particular for the queueing effects under the finite blocklength regime. A recently developed methodology provides probabilistic higher-layer delay bounds for fading channels when assuming transmission at the Shannon capacity limit. Based on this novel approach, we develop service process characterizations for fading channels with finite blocklength channel coding, leading to novel probabilistic delay bounds that can give a fundamental insight into the capabilities and limitations of wireless networks when facing low-latency M2M applications. In particular, we show that the Shannon capacity model significantly overestimates the delay performance for such applications, which would lead to insufficient resource allocations. Finally, based on our (validated) analytical model, we study various important parameter trade-offs highlighting the sensitivity of the delay distribution under the finite blocklength regime., Qc 20160323

Optimal power allocation in a multi-hop cognitive radio network is investigated. Information transmitted from the source passes through several wireless relay nodes before reaching the destination. At each hop, the received signal is decoded, re-encoded and retransmitted to the following node. Transmissions at every hop are overheard by nearby nodes and therefore cause interference. We study optimal power allocation strategies that maximize the end-to-end throughput of the network under the constraint of strictly limited interference to external users. We show that for networks that can be modeled as a line topology the optimal solution is achieved when the capacities of every intermediate link are equal and the interference power constraint is satisfied with equality. High-and low-SNR approximations that simplify the problem of finding the optimal power allocation are presented as well. The numerical results show good performance compared to schemes with equal power allocation., QC 20111201

Optimal power allocation in a multi-hop cognitive radio network is investigated. Information transmitted from the source passes through several wireless relay nodes before reaching the destination. At each hop, the received signal is decoded, re-encoded and retransmitted to the following node. Transmissions at every hop are overheard by nearby nodes and therefore cause interference. We study optimal power allocation strategies that maximize the end-to-end throughput of the network under the constraint of strictly limited interference to external users. We show that for networks that can be modeled as a line topology the optimal solution is achieved when the capacities of every intermediate link are equal and the interference power constraint is satisfied with equality. High-and low-SNR approximations that simplify the problem of finding the optimal power allocation are presented as well. The numerical results show good performance compared to schemes with equal power allocation., QC 20111201

We investigate the capacity bounds for a wireless multicast relay network where two sources simultaneously multicast to two destinations through Gaussian channels with the help of a full-duplex relay node. All the individual channel gains are assumed to be time-invariant and known to every nodes in the network. The transmissions from two sources and from the relay use the same channel resource (i.e. co-channel transmission) and the two source nodes are connected with an orthogonal error-free backhaul. This multicast relay network is generic in the sense that it can be extended to more general networks by tuning the channel gains within the range [0, ∞). By extending the proof of the converse developed by Cover and El Gamal for the Gaussian relay channel, we characterize the cut-set bound for this multicast relay network. We also present a lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111030, VINNOVA/MOST joint IMT-Advanced Project

Optimal power allocation in a multi-hop cognitive radio network is investigated. Information transmitted from the source passes through several wireless relay nodes before reaching the destination. At each hop, the received signal is decoded, re-encoded and retransmitted to the following node. Transmissions at every hop are overheard by nearby nodes and therefore cause interference. We study optimal power allocation strategies that maximize the end-to-end throughput of the network under the constraint of strictly limited interference to external users. We show that for networks that can be modeled as a line topology the optimal solution is achieved when the capacities of every intermediate link are equal and the interference power constraint is satisfied with equality. High-and low-SNR approximations that simplify the problem of finding the optimal power allocation are presented as well. The numerical results show good performance compared to schemes with equal power allocation., QC 20111201

We investigate the capacity bounds for a wireless multicast relay network where two sources simultaneously multicast to two destinations through Gaussian channels with the help of a full-duplex relay node. All the individual channel gains are assumed to be time-invariant and known to every nodes in the network. The transmissions from two sources and from the relay use the same channel resource (i.e. co-channel transmission) and the two source nodes are connected with an orthogonal error-free backhaul. This multicast relay network is generic in the sense that it can be extended to more general networks by tuning the channel gains within the range [0, ∞). By extending the proof of the converse developed by Cover and El Gamal for the Gaussian relay channel, we characterize the cut-set bound for this multicast relay network. We also present a lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111030, VINNOVA/MOST joint IMT-Advanced Project

We investigate the capacity bounds for a wireless multicast relay network where two sources simultaneously multicast to two destinations through Gaussian channels with the help of a full-duplex relay node. All the individual channel gains are assumed to be time-invariant and known to every nodes in the network. The transmissions from two sources and from the relay use the same channel resource (i.e. co-channel transmission) and the two source nodes are connected with an orthogonal error-free backhaul. This multicast relay network is generic in the sense that it can be extended to more general networks by tuning the channel gains within the range [0, ∞). By extending the proof of the converse developed by Cover and El Gamal for the Gaussian relay channel, we characterize the cut-set bound for this multicast relay network. We also present a lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111030, VINNOVA/MOST joint IMT-Advanced Project

Optimal power allocation in a multi-hop cognitive radio network is investigated. Information transmitted from the source passes through several wireless relay nodes before reaching the destination. At each hop, the received signal is decoded, re-encoded and retransmitted to the following node. Transmissions at every hop are overheard by nearby nodes and therefore cause interference. We study optimal power allocation strategies that maximize the end-to-end throughput of the network under the constraint of strictly limited interference to external users. We show that for networks that can be modeled as a line topology the optimal solution is achieved when the capacities of every intermediate link are equal and the interference power constraint is satisfied with equality. High-and low-SNR approximations that simplify the problem of finding the optimal power allocation are presented as well. The numerical results show good performance compared to schemes with equal power allocation., QC 20111201

Optimal power allocation in a multi-hop cognitive radio network is investigated. Information transmitted from the source passes through several wireless relay nodes before reaching the destination. At each hop, the received signal is decoded, re-encoded and retransmitted to the following node. Transmissions at every hop are overheard by nearby nodes and therefore cause interference. We study optimal power allocation strategies that maximize the end-to-end throughput of the network under the constraint of strictly limited interference to external users. We show that for networks that can be modeled as a line topology the optimal solution is achieved when the capacities of every intermediate link are equal and the interference power constraint is satisfied with equality. High-and low-SNR approximations that simplify the problem of finding the optimal power allocation are presented as well. The numerical results show good performance compared to schemes with equal power allocation., QC 20111201

We investigate the capacity bounds for a wireless multicast relay network where two sources simultaneously multicast to two destinations through Gaussian channels with the help of a full-duplex relay node. All the individual channel gains are assumed to be time-invariant and known to every nodes in the network. The transmissions from two sources and from the relay use the same channel resource (i.e. co-channel transmission) and the two source nodes are connected with an orthogonal error-free backhaul. This multicast relay network is generic in the sense that it can be extended to more general networks by tuning the channel gains within the range [0, ∞). By extending the proof of the converse developed by Cover and El Gamal for the Gaussian relay channel, we characterize the cut-set bound for this multicast relay network. We also present a lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111030, VINNOVA/MOST joint IMT-Advanced Project

We investigate the capacity bounds for a wireless multicast relay network where two sources simultaneously multicast to two destinations through Gaussian channels with the help of a full-duplex relay node. All the individual channel gains are assumed to be time-invariant and known to every nodes in the network. The transmissions from two sources and from the relay use the same channel resource (i.e. co-channel transmission) and the two source nodes are connected with an orthogonal error-free backhaul. This multicast relay network is generic in the sense that it can be extended to more general networks by tuning the channel gains within the range [0, ∞). By extending the proof of the converse developed by Cover and El Gamal for the Gaussian relay channel, we characterize the cut-set bound for this multicast relay network. We also present a lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111030, VINNOVA/MOST joint IMT-Advanced Project

Optimal power allocation in a multi-hop cognitive radio network is investigated. Information transmitted from the source passes through several wireless relay nodes before reaching the destination. At each hop, the received signal is decoded, re-encoded and retransmitted to the following node. Transmissions at every hop are overheard by nearby nodes and therefore cause interference. We study optimal power allocation strategies that maximize the end-to-end throughput of the network under the constraint of strictly limited interference to external users. We show that for networks that can be modeled as a line topology the optimal solution is achieved when the capacities of every intermediate link are equal and the interference power constraint is satisfied with equality. High-and low-SNR approximations that simplify the problem of finding the optimal power allocation are presented as well. The numerical results show good performance compared to schemes with equal power allocation., QC 20111201

We investigate the capacity bounds for relay-aided two-source two-destination wireless networks with backhaul support between source nodes. Each source multicasts its own message to all destinations with the help of an intermediate relay node, which is full-duplex and shared by both sources. We are aiming to characterize the capacity region of this model given discrete memoryless Gaussian channels. We establish three capacity upper bounds by relaxing the cut-set bound, and by extending two capacity bounds originally derived for MIMO relay channels. We also present one lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111108, VINNOVA/MOST joint IMT-Advanced Project

We investigate cooperative strategies for relay-aided multi-source multi-destination wireless networks with backhaul support. Each source multicasts information to all destinations using a shared relay. We study cooperative strategies based on different network coding (NC) schemes, namely, finite field NC (FNC), linear NC (LNC), and lattice coding. To further exploit the backhaul connection, we also propose NC-based beam-forming (NBF). We measure the performance in term of achievable rates over Gaussian channels and observe significant gains over a benchmark scheme. The benefit of using backhaul is also clearly demonstrated in most of scenarios., QC 20111115, VINNOVA/MOST joint IMT-Advanced Project

We investigate the capacity bounds for relay-aided two-source two-destination wireless networks with backhaul support between source nodes. Each source multicasts its own message to all destinations with the help of an intermediate relay node, which is full-duplex and shared by both sources. We are aiming to characterize the capacity region of this model given discrete memoryless Gaussian channels. We establish three capacity upper bounds by relaxing the cut-set bound, and by extending two capacity bounds originally derived for MIMO relay channels. We also present one lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111108, VINNOVA/MOST joint IMT-Advanced Project

We investigate cooperative strategies for relay-aided multi-source multi-destination wireless networks with backhaul support. Each source multicasts information to all destinations using a shared relay. We study cooperative strategies based on different network coding (NC) schemes, namely, finite field NC (FNC), linear NC (LNC), and lattice coding. To further exploit the backhaul connection, we also propose NC-based beam-forming (NBF). We measure the performance in term of achievable rates over Gaussian channels and observe significant gains over a benchmark scheme. The benefit of using backhaul is also clearly demonstrated in most of scenarios., QC 20111115, VINNOVA/MOST joint IMT-Advanced Project

We investigate the capacity bounds for relay-aided two-source two-destination wireless networks with backhaul support between source nodes. Each source multicasts its own message to all destinations with the help of an intermediate relay node, which is full-duplex and shared by both sources. We are aiming to characterize the capacity region of this model given discrete memoryless Gaussian channels. We establish three capacity upper bounds by relaxing the cut-set bound, and by extending two capacity bounds originally derived for MIMO relay channels. We also present one lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111108, VINNOVA/MOST joint IMT-Advanced Project

We investigate cooperative strategies for relay-aided multi-source multi-destination wireless networks with backhaul support. Each source multicasts information to all destinations using a shared relay. We study cooperative strategies based on different network coding (NC) schemes, namely, finite field NC (FNC), linear NC (LNC), and lattice coding. To further exploit the backhaul connection, we also propose NC-based beam-forming (NBF). We measure the performance in term of achievable rates over Gaussian channels and observe significant gains over a benchmark scheme. The benefit of using backhaul is also clearly demonstrated in most of scenarios., QC 20111115, VINNOVA/MOST joint IMT-Advanced Project

We investigate the capacity bounds for relay-aided two-source two-destination wireless networks with backhaul support between source nodes. Each source multicasts its own message to all destinations with the help of an intermediate relay node, which is full-duplex and shared by both sources. We are aiming to characterize the capacity region of this model given discrete memoryless Gaussian channels. We establish three capacity upper bounds by relaxing the cut-set bound, and by extending two capacity bounds originally derived for MIMO relay channels. We also present one lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111108, VINNOVA/MOST joint IMT-Advanced Project

We investigate cooperative strategies for relay-aided multi-source multi-destination wireless networks with backhaul support. Each source multicasts information to all destinations using a shared relay. We study cooperative strategies based on different network coding (NC) schemes, namely, finite field NC (FNC), linear NC (LNC), and lattice coding. To further exploit the backhaul connection, we also propose NC-based beam-forming (NBF). We measure the performance in term of achievable rates over Gaussian channels and observe significant gains over a benchmark scheme. The benefit of using backhaul is also clearly demonstrated in most of scenarios., QC 20111115, VINNOVA/MOST joint IMT-Advanced Project

We investigate the capacity bounds for relay-aided two-source two-destination wireless networks with backhaul support between source nodes. Each source multicasts its own message to all destinations with the help of an intermediate relay node, which is full-duplex and shared by both sources. We are aiming to characterize the capacity region of this model given discrete memoryless Gaussian channels. We establish three capacity upper bounds by relaxing the cut-set bound, and by extending two capacity bounds originally derived for MIMO relay channels. We also present one lower bound by using decoding-and-forward relaying combined with network beam-forming., QC 20111108, VINNOVA/MOST joint IMT-Advanced Project

We investigate cooperative strategies for relay-aided multi-source multi-destination wireless networks with backhaul support. Each source multicasts information to all destinations using a shared relay. We study cooperative strategies based on different network coding (NC) schemes, namely, finite field NC (FNC), linear NC (LNC), and lattice coding. To further exploit the backhaul connection, we also propose NC-based beam-forming (NBF). We measure the performance in term of achievable rates over Gaussian channels and observe significant gains over a benchmark scheme. The benefit of using backhaul is also clearly demonstrated in most of scenarios., QC 20111115, VINNOVA/MOST joint IMT-Advanced Project