52 research outputs found
Advanced interference management techniques for future wireless networks
In this thesis, we design advanced interference management techniques for future wireless
networks under the availability of perfect and imperfect channel state information
(CSI). We do so by considering a generalized imperfect CSI model where the variance of
the channel estimation error depends on the signal-to-noise ratio (SNR).
First, we analyze the performance of standard linear precoders, namely channel inversion
(CI) and regularized CI (RCI), in downlink of cellular networks by deriving the
received signal-to-interference-plus-noise ratio (SINR) of each user subject to both perfect
and imperfect CSI. In this case, novel bounds on the asymptotic performance of linear precoders
are derived, which determine howmuch accurate CSI should be to achieve a certain
quality of service (QoS). By relying on the knowledge of error variance in advance, we
propose an adaptive RCI technique to further improve the performance of standard RCI
subject to CSI mismatch.
We further consider transmit-power efficient design of wireless cellular networks. We
propose two novel linear precoding techniques which can notably decrease the deployed
power at transmit side in order to secure the same average output SINR at each user compared
to standard linear precoders like CI and RCI.
We also address a more sophisticated interference scenario, i.e., wireless interference
networks, wherein each of the K transmitters communicates with its corresponding receiver
while causing interference to the others. The most representative interference
management technique in this case is interference alignment (IA). Unlike standard techniques
like time division multiple access (TDMA) and frequency division multiple access
(FDMA) where the achievable degrees of freedom (DoF) is one, with IA, the achievable
DoF scales up with the number of users. Therefore, in this thesis, we quantify the
asymptotic performance of IA under a generalized CSI mismatch model by deriving novel
bounds on asymptotic mean loss in sum rate and the achievable DoF. We also propose
novel least squares (LS) and minimum mean square error (MMSE) based IA techniques
which are able to outperform standard IA schemes under perfect and imperfect CSI. Furthermore,
we consider the implementation of IA in coordinated networks which enable us
to decrease the number of deployed antennas in order to secure the same achievable DoF
compared to standard IA techniques
Min-Max MSE-based Interference Alignment for Transceiver Designs in Cognitive Radio Networks
This paper is concerned with an optimal design of the precoders and receive filters for cognitive radio (CR) networks in which multiple secondary users (SUs) share the same frequency band with multiple primary users (PUs). To cope with interference and to achieve fairness among users, we develop an interference alignment (IA) scheme by minimizing the maximum mean squared error (Min-Max MSE) of the received signals. Since the Min-Max MSE design problems are nonconvex in the design matrix variables of the precoders and receive filters, we develop an alternating optimization algorithm with provable convergence to iteratively find the optimal solutions. In each iteration, the precoder design problems can be recast as second order cone program (SOCP) while the optimal receive filters can be derived in closed-form solutions. Finally, numerical results are provided to demonstrate the superiority of the proposed method as compared to previous work in terms of the information rate and bit error rate
Joint transceiver design and power optimization for wireless sensor networks in underground mines
Avec les grands dĂ©veloppements des technologies de communication sans fil, les rĂ©seaux de capteurs sans fil (WSN) ont attirĂ© beaucoup dâattention dans le monde entier au cours de la derniĂšre dĂ©cennie. Les rĂ©seaux de capteurs sans fil sont maintenant utilisĂ©s pour a surveillance sanitaire, la gestion des catastrophes, la dĂ©fense, les tĂ©lĂ©communications, etc. De tels rĂ©seaux sont utilisĂ©s dans de nombreuses applications industrielles et commerciales comme la surveillance des processus industriels et de lâenvironnement, etc. Un rĂ©seau WSN est une collection de transducteurs spĂ©cialisĂ©s connus sous le nom de noeuds de capteurs avec une liaison de communication distribuĂ©e de maniĂšre alĂ©atoire dans tous les emplacements pour surveiller les paramĂštres. Chaque noeud de capteur est Ă©quipĂ© dâun transducteur, dâun processeur de signal, dâune unitĂ© dâalimentation et dâun Ă©metteur-rĂ©cepteur. Les WSN sont maintenant largement utilisĂ©s dans lâindustrie miniĂšre souterraine pour surveiller certains paramĂštres environnementaux, comme la quantitĂ© de gaz, dâeau, la tempĂ©rature, lâhumiditĂ©, le niveau dâoxygĂšne, de poussiĂšre, etc. Dans le cas de la surveillance de lâenvironnement, un WSN peut ĂȘtre remplacĂ© de maniĂšre Ă©quivalente par un rĂ©seau Ă relais Ă entrĂ©es et sorties multiples (MIMO). Les rĂ©seaux de relais multisauts ont attirĂ© un intĂ©rĂȘt de recherche important ces derniers temps grĂące Ă leur capacitĂ© Ă augmenter la portĂ©e de la couverture. La liaison de communication rĂ©seau dâune source vers une destination est mise en oeuvre en utilisant un schĂ©ma dâamplification/transmission (AF) ou de dĂ©codage/transfert (DF). Le relais AF reçoit des informations du relais prĂ©cĂ©dent et amplifie simplement le signal reçu, puis il le transmet au relais suivant. Dâautre part, le relais DF dĂ©code dâabord le signal reçu, puis il le transmet au relais suivant au deuxiĂšme Ă©tage sâil peut parfaitement dĂ©coder le signal entrant. En raison de la simplicitĂ© analytique, dans cette thĂšse, nous considĂ©rons le schĂ©ma de relais AF et les rĂ©sultats de ce travail peuvent Ă©galement ĂȘtre dĂ©veloppĂ©s pour le relais DF. La conception dâun Ă©metteur/rĂ©cepteur pour le relais MIMO multisauts est trĂšs difficile. Car Ă lâĂ©tape de relais L, il y a 2L canaux possibles. Donc, pour un rĂ©seau Ă grande Ă©chelle, il nâest pas Ă©conomique dâenvoyer un signal par tous les liens possibles. Au lieu de cela, nous pouvons trouver le meilleur chemin de la source Ă la destination qui donne le rapport signal sur bruit (SNR) de bout en bout le plus Ă©levĂ©. Nous pouvons minimiser la fonction objectif dâerreur quadratique moyenne (MSE) ou de taux dâerreur binaire (BER) en envoyant le signal utilisant le chemin sĂ©lectionnĂ©. Lâensemble de relais dans le chemin reste actif et le reste des relais sâĂ©teint, ce qui permet dâĂ©conomiser de lâĂ©nergie afin dâamĂ©liorer la durĂ©e de vie du rĂ©seau. Le meilleur chemin de transmission de signal a Ă©tĂ© Ă©tudiĂ© dans la littĂ©rature pour un relais MIMO Ă deux bonds mais est plus complexe pour un ...With the great developments in wireless communication technologies, Wireless Sensor Networks (WSNs) have gained attention worldwide in the past decade and are now being used in health monitoring, disaster management, defense, telecommunications, etc. Such networks are used in many industrial and consumer applications such as industrial process and environment monitoring, among others. A WSN network is a collection of specialized transducers known as sensor nodes with a communication link distributed randomly in any locations to monitor environmental parameters such as water level, and temperature. Each sensor node is equipped with a transducer, a signal processor, a power unit, and a transceiver. WSNs are now being widely used in the underground mining industry to monitor environmental parameters, including the amount of gas, water, temperature, humidity, oxygen level, dust, etc. The WSN for environment monitoring can be equivalently replaced by a multiple-input multiple-output (MIMO) relay network. Multi-hop relay networks have attracted significant research interest in recent years for their capability in increasing the coverage range. The network communication link from a source to a destination is implemented using the amplify-and-forward (AF) or decode-and-forward (DF) schemes. The AF relay receives information from the previous relay and simply amplifies the received signal and then forwards it to the next relay. On the other hand, the DF relay first decodes the received signal and then forwards it to the next relay in the second stage if it can perfectly decode the incoming signal. For analytical simplicity, in this thesis, we consider the AF relaying scheme and the results of this work can also be developed for the DF relay. The transceiver design for multi-hop MIMO relay is very challenging. This is because at the L-th relay stage, there are 2L possible channels. So, for a large scale network, it is not economical to send the signal through all possible links. Instead, we can find the best path from source-to-destination that gives the highest end-to-end signal-to-noise ratio (SNR). We can minimize the mean square error (MSE) or bit error rate (BER) objective function by sending the signal using the selected path. The set of relay in the path remains active and the rest of the relays are turned off which can save power to enhance network life-time. The best path signal transmission has been carried out in the literature for 2-hop MIMO relay and for multiple relaying it becomes very complex. In the first part of this thesis, we propose an optimal best path finding algorithm at perfect channel state information (CSI). We consider a parallel multi-hop multiple-input multiple-output (MIMO) AF relay system where a linear minimum mean-squared error (MMSE) receiver is used at the destination. We simplify the parallel network into equivalent series multi-hop MIMO relay link using best relaying, where the best relay ..
Integrated Sensing and Communications: Recent Advances and Ten Open Challenges
It is anticipated that integrated sensing and communications (ISAC) would be
one of the key enablers of next-generation wireless networks (such as beyond 5G
(B5G) and 6G) for supporting a variety of emerging applications. In this paper,
we provide a comprehensive review of the recent advances in ISAC systems, with
a particular focus on their foundations, system design, networking aspects and
ISAC applications. Furthermore, we discuss the corresponding open questions of
the above that emerged in each issue. Hence, we commence with the information
theory of sensing and communications (SC), followed by the
information-theoretic limits of ISAC systems by shedding light on the
fundamental performance metrics. Next, we discuss their clock synchronization
and phase offset problems, the associated Pareto-optimal signaling strategies,
as well as the associated super-resolution ISAC system design. Moreover, we
envision that ISAC ushers in a paradigm shift for the future cellular networks
relying on network sensing, transforming the classic cellular architecture,
cross-layer resource management methods, and transmission protocols. In ISAC
applications, we further highlight the security and privacy issues of wireless
sensing. Finally, we close by studying the recent advances in a representative
ISAC use case, namely the multi-object multi-task (MOMT) recognition problem
using wireless signals.Comment: 26 pages, 22 figures, resubmitted to IEEE Journal. Appreciation for
the outstanding contributions of coauthors in the paper
Interference alignment at intermediate SNR with perfect or noisy CSI
Interference alignment is a new technique combining transmitter precoding and receiver interference suppression to achieve the optimal multiplexing gain in interference networks by exploiting knowledge of channel state information of all transmission links. So far closed form solutions for the transmit filters have only been found in certain cases. Also the feasibility of interference alignment schemes based on symbol extensions, over a limited number of signalling dimensions, is still an open problem.
In this work we investigate the performance in terms of bit error rates, of interference alignment schemes at intermediate signal-to-noise ratios, through Monte Carlo simulations. We focus our attention on the three and four users time-varying interference channel, using both the closed form solutions
known at present as well as iterative algorithms. We then investigate the impact of noisy channel state information on the performances of some of the interference alignment systems considered.
In the single input single output interference channel the closed form solutions of the interference alignment cause considerably different bit error rates for the different nodes in the network. In the multiple input multiple output interference channel we exhibit that bit error rate saturates at moderate signal-to-noise ratios when interference alignment schemes are infeasible
and even when they are feasible, some of the analyzed algorithms show unpredictable behaviors by deteriorating the performance as the signal-to-noise ratio exceeds a threshold. Further renements are necessary in order to obtain better bit error rates in these cases. We evince that additional
improvements are also needed to the original interference alignment schemes in order to mitigate their sensitivity to noisy channel state informatio
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